{"id":97888,"date":"2026-09-25T11:07:46","date_gmt":"2026-09-25T08:07:46","guid":{"rendered":"https:\/\/twodots.gr\/?p=97888"},"modified":"2026-09-25T11:07:48","modified_gmt":"2026-09-25T08:07:48","slug":"explainable-ai-xronoseires-frameworks","status":"publish","type":"post","link":"https:\/\/twodots.gr\/en\/explainable-ai-xronoseires-frameworks\/","title":{"rendered":"Explainable AI \u03c3\u03c4\u03b9\u03c2 \u03c7\u03c1\u03bf\u03bd\u03bf\u03c3\u03b5\u03b9\u03c1\u03ad\u03c2: \u03cc\u03c4\u03b1\u03bd \u03c4\u03bf \u03af\u03b4\u03b9\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03b4\u03af\u03bd\u03b5\u03b9 \u03ac\u03bb\u03bb\u03b7 \u03b5\u03be\u03ae\u03b3\u03b7\u03c3\u03b7"},"content":{"rendered":"<div class=\"td-article-lede\">\n<p><strong>Answer first:<\/strong> \u03c4\u03bf explainable AI \u03c3\u03c4\u03b9\u03c2 \u03c7\u03c1\u03bf\u03bd\u03bf\u03c3\u03b5\u03b9\u03c1\u03ad\u03c2 \u03b4\u03b5\u03bd \u03b1\u03be\u03b9\u03bf\u03bb\u03bf\u03b3\u03b5\u03af\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc \u03c4\u03bf \u03b1\u03bd \u03c0\u03b1\u03c1\u03ac\u03b3\u03b5\u03b9 \u03ad\u03bd\u03b1 \u03c0\u03b5\u03b9\u03c3\u03c4\u03b9\u03ba\u03cc heatmap, \u03b1\u03bb\u03bb\u03ac \u03b1\u03c0\u03cc \u03c4\u03bf \u03b1\u03bd \u03b7 \u03b5\u03be\u03ae\u03b3\u03b7\u03c3\u03b7 \u03c3\u03ad\u03b2\u03b5\u03c4\u03b1\u03b9 \u03c4\u03bf\u03bd \u03c7\u03c1\u03cc\u03bd\u03bf, \u03c4\u03b1 \u03ba\u03b1\u03bd\u03ac\u03bb\u03b9\u03b1 \u03ba\u03b1\u03b9 \u03c4\u03bf \u03ba\u03b1\u03c4\u03ac\u03bb\u03bb\u03b7\u03bb\u03bf domain \u03c4\u03bf\u03c5 \u03c3\u03ae\u03bc\u03b1\u03c4\u03bf\u03c2 \u03ba\u03b1\u03b9 \u03b1\u03bd \u03b1\u03bd\u03b1\u03c0\u03b1\u03c1\u03ac\u03b3\u03b5\u03c4\u03b1\u03b9 \u03bc\u03b5 \u03ba\u03b1\u03c4\u03b1\u03b3\u03b5\u03b3\u03c1\u03b1\u03bc\u03bc\u03ad\u03bd\u03bf framework, \u03ad\u03ba\u03b4\u03bf\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03c0\u03b1\u03c1\u03b1\u03bc\u03ad\u03c4\u03c1\u03bf\u03c5\u03c2.<\/p>\n<p>\u0397 \u03c3\u03c5\u03c3\u03c4\u03b7\u03bc\u03b1\u03c4\u03b9\u03ba\u03ae \u03b1\u03bd\u03b1\u03c3\u03ba\u03cc\u03c0\u03b7\u03c3\u03b7 \u03ad\u03be\u03b9 XAI frameworks \u03b2\u03c1\u03ae\u03ba\u03b5 51 \u03bc\u03b5\u03b8\u03cc\u03b4\u03bf\u03c5\u03c2 \u03ba\u03b1\u03b9 52 metrics, \u03b1\u03bb\u03bb\u03ac \u03bc\u03cc\u03bd\u03bf 16 \u03bc\u03ad\u03b8\u03bf\u03b4\u03bf\u03b9 \u03ba\u03b1\u03b9 \u03b4\u03cd\u03bf metrics \u03b5\u03af\u03c7\u03b1\u03bd \u03c3\u03c7\u03b5\u03b4\u03b9\u03b1\u03c3\u03c4\u03b5\u03af \u03b5\u03b9\u03b4\u03b9\u03ba\u03ac \u03b3\u03b9\u03b1 \u03c7\u03c1\u03bf\u03bd\u03bf\u03c3\u03b5\u03b9\u03c1\u03ad\u03c2. \u03a3\u03c4\u03bf \u03c0\u03b5\u03af\u03c1\u03b1\u03bc\u03b1 ECG, \u03b4\u03cd\u03bf \u03c5\u03bb\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03b5\u03b9\u03c2 \u03c4\u03bf\u03c5 \u03af\u03b4\u03b9\u03bf\u03c5 Integrated Gradients \u03bc\u03b5 \u03af\u03b4\u03b9\u03b5\u03c2 \u03b5\u03bc\u03c6\u03b1\u03bd\u03b5\u03af\u03c2 \u03c0\u03b1\u03c1\u03b1\u03bc\u03ad\u03c4\u03c1\u03bf\u03c5\u03c2 \u03ad\u03b4\u03c9\u03c3\u03b1\u03bd \u03c3\u03c5\u03c3\u03c4\u03b7\u03bc\u03b1\u03c4\u03b9\u03ba\u03ac \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03ad\u03c2 \u03b5\u03be\u03b7\u03b3\u03ae\u03c3\u03b5\u03b9\u03c2. \u0393\u03b9\u03b1 \u03bc\u03b9\u03b1 \u03b5\u03c0\u03b9\u03c7\u03b5\u03af\u03c1\u03b7\u03c3\u03b7, \u03b1\u03c5\u03c4\u03cc \u03bc\u03b5\u03c4\u03b1\u03c4\u03c1\u03ad\u03c0\u03b5\u03b9 \u03c4\u03bf XAI \u03b1\u03c0\u03cc \u03bf\u03c0\u03c4\u03b9\u03ba\u03cc \u03c0\u03c1\u03cc\u03c3\u03b8\u03b5\u03c4\u03bf \u03c3\u03b5 \u03b5\u03bb\u03b5\u03b3\u03c7\u03cc\u03bc\u03b5\u03bd\u03bf software pipeline.<\/p>\n<\/div>\n<div class=\"td-article-toc\">\n<div class=\"td-toc-title\">Contents<\/div>\n<ul>\n<li><a href=\"#xronoseires-diaforetiki-exigisi\">\u0393\u03b9\u03b1\u03c4\u03af \u03bf\u03b9 \u03c7\u03c1\u03bf\u03bd\u03bf\u03c3\u03b5\u03b9\u03c1\u03ad\u03c2 \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03bf\u03bd\u03c4\u03b1\u03b9 \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03ae \u03b5\u03be\u03ae\u03b3\u03b7\u03c3\u03b7<\/a><\/li>\n<li><a href=\"#exi-xai-frameworks\">\u03a0\u03ce\u03c2 \u03b5\u03bd\u03c4\u03bf\u03c0\u03af\u03c3\u03c4\u03b7\u03ba\u03b1\u03bd \u03c4\u03b1 \u03ad\u03be\u03b9 XAI frameworks<\/a><\/li>\n<li><a href=\"#ti-prosferei-kathe-framework\">\u03a4\u03b9 \u03c0\u03c1\u03bf\u03c3\u03c6\u03ad\u03c1\u03b5\u03b9 \u03ba\u03ac\u03b8\u03b5 framework \u03c3\u03c4\u03b7\u03bd \u03c0\u03c1\u03ac\u03be\u03b7<\/a><\/li>\n<li><a href=\"#methodoi-xroniki-exeidikefsi\">\u039f\u03b9 51 \u03bc\u03ad\u03b8\u03bf\u03b4\u03bf\u03b9 \u03ba\u03b1\u03b9 \u03c4\u03bf \u03ba\u03b5\u03bd\u03cc \u03c4\u03b7\u03c2 \u03c7\u03c1\u03bf\u03bd\u03b9\u03ba\u03ae\u03c2 \u03b5\u03be\u03b5\u03b9\u03b4\u03af\u03ba\u03b5\u03c5\u03c3\u03b7\u03c2<\/a><\/li>\n<li><a href=\"#syxnotites-dft-lrp\">\u03a4\u03bf \u03c3\u03c7\u03b5\u03b4\u03cc\u03bd \u03ac\u03b4\u03b5\u03b9\u03bf \u03c0\u03b5\u03b4\u03af\u03bf \u03c4\u03c9\u03bd \u03c3\u03c5\u03c7\u03bd\u03bf\u03c4\u03ae\u03c4\u03c9\u03bd<\/a><\/li>\n<li><a href=\"#cross-channel-dependencies\">\u039f\u03b9 \u03c3\u03c7\u03ad\u03c3\u03b5\u03b9\u03c2 \u03b1\u03bd\u03ac\u03bc\u03b5\u03c3\u03b1 \u03c3\u03c4\u03b1 \u03ba\u03b1\u03bd\u03ac\u03bb\u03b9\u03b1<\/a><\/li>\n<li><a href=\"#metrics-time-series\">52 metrics, \u03b1\u03bb\u03bb\u03ac \u03bc\u03cc\u03bd\u03bf \u03b4\u03cd\u03bf \u03b5\u03b9\u03b4\u03b9\u03ba\u03ac \u03b3\u03b9\u03b1 time series<\/a><\/li>\n<li><a href=\"#benchmarks-ground-truth\">Benchmarks \u03ba\u03b1\u03b9 \u03c4\u03bf \u03c0\u03c1\u03cc\u03b2\u03bb\u03b7\u03bc\u03b1 \u03c4\u03bf\u03c5 ground truth<\/a><\/li>\n<li><a href=\"#framework-allazei-exigisi\">\u038c\u03c4\u03b1\u03bd \u03c4\u03bf framework \u03b1\u03bb\u03bb\u03ac\u03b6\u03b5\u03b9 \u03c4\u03b7\u03bd \u03b5\u03be\u03ae\u03b3\u03b7\u03c3\u03b7<\/a><\/li>\n<li><a href=\"#provenance-governance\">\u03a4\u03b9 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03ba\u03b1\u03c4\u03b1\u03b3\u03c1\u03ac\u03c6\u03b5\u03b9 \u03bc\u03b9\u03b1 \u03b5\u03c0\u03b9\u03c7\u03b5\u03af\u03c1\u03b7\u03c3\u03b7<\/a><\/li>\n<li><a href=\"#epta-vimata-xai-pilot\">\u0395\u03c0\u03c4\u03ac \u03b2\u03ae\u03bc\u03b1\u03c4\u03b1 \u03b3\u03b9\u03b1 \u03b5\u03bb\u03b5\u03b3\u03c7\u03cc\u03bc\u03b5\u03bd\u03bf XAI pilot<\/a><\/li>\n<li><a href=\"#periorismoi-symperasma\">\u03a0\u03b5\u03c1\u03b9\u03bf\u03c1\u03b9\u03c3\u03bc\u03bf\u03af \u03ba\u03b1\u03b9 \u03c0\u03c1\u03b1\u03ba\u03c4\u03b9\u03ba\u03cc \u03c3\u03c5\u03bc\u03c0\u03ad\u03c1\u03b1\u03c3\u03bc\u03b1<\/a><\/li>\n<\/ul>\n<\/div>\n<h2 id=\"xronoseires-diaforetiki-exigisi\">\u0393\u03b9\u03b1\u03c4\u03af \u03bf\u03b9 \u03c7\u03c1\u03bf\u03bd\u03bf\u03c3\u03b5\u03b9\u03c1\u03ad\u03c2 \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03bf\u03bd\u03c4\u03b1\u03b9 \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03ae \u03b5\u03be\u03ae\u03b3\u03b7\u03c3\u03b7<\/h2>\n<p>\u0388\u03bd\u03b1 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03c4\u03b1\u03be\u03b9\u03bd\u03bf\u03bc\u03b5\u03af \u03c3\u03c9\u03c3\u03c4\u03ac \u03ad\u03bd\u03b1 \u03b7\u03bb\u03b5\u03ba\u03c4\u03c1\u03bf\u03ba\u03b1\u03c1\u03b4\u03b9\u03bf\u03b3\u03c1\u03ac\u03c6\u03b7\u03bc\u03b1, \u03ad\u03bd\u03b1 \u03b2\u03b9\u03bf\u03bc\u03b7\u03c7\u03b1\u03bd\u03b9\u03ba\u03cc \u03c3\u03ae\u03bc\u03b1 \u03ae \u03bc\u03b9\u03b1 \u03b1\u03ba\u03bf\u03bb\u03bf\u03c5\u03b8\u03af\u03b1 \u03bc\u03b5\u03c4\u03c1\u03ae\u03c3\u03b5\u03c9\u03bd. \u03a4\u03bf \u03b4\u03cd\u03c3\u03ba\u03bf\u03bb\u03bf \u03b5\u03c1\u03ce\u03c4\u03b7\u03bc\u03b1 \u03b1\u03c1\u03c7\u03af\u03b6\u03b5\u03b9 \u03bc\u03b5\u03c4\u03ac \u03c4\u03b7\u03bd \u03c0\u03c1\u03cc\u03b2\u03bb\u03b5\u03c8\u03b7: \u03c0\u03bf\u03b9\u03b1 \u03c7\u03c1\u03bf\u03bd\u03b9\u03ba\u03ac \u03c3\u03b7\u03bc\u03b5\u03af\u03b1, \u03c7\u03b1\u03c1\u03b1\u03ba\u03c4\u03b7\u03c1\u03b9\u03c3\u03c4\u03b9\u03ba\u03ac \u03ae \u03c3\u03c7\u03ad\u03c3\u03b5\u03b9\u03c2 \u03bf\u03b4\u03ae\u03b3\u03b7\u03c3\u03b1\u03bd \u03c3\u03c4\u03bf \u03b1\u03c0\u03bf\u03c4\u03ad\u03bb\u03b5\u03c3\u03bc\u03b1 \u03ba\u03b1\u03b9 \u03b8\u03b1 \u03c0\u03b1\u03c1\u03b1\u03bc\u03b5\u03af\u03bd\u03b5\u03b9 \u03b7 \u03b5\u03be\u03ae\u03b3\u03b7\u03c3\u03b7 \u03af\u03b4\u03b9\u03b1 \u03b1\u03bd \u03b7 \u03bf\u03bc\u03ac\u03b4\u03b1 \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03b5\u03b9 \u03ac\u03bb\u03bb\u03b7 \u03b2\u03b9\u03b2\u03bb\u03b9\u03bf\u03b8\u03ae\u03ba\u03b7 \u03b3\u03b9\u03b1 \u03c4\u03b7\u03bd \u03af\u03b4\u03b9\u03b1 \u03bc\u03ad\u03b8\u03bf\u03b4\u03bf;<\/p>\n<p>\u03a7\u03c1\u03bf\u03bd\u03bf\u03c3\u03b5\u03b9\u03c1\u03ac \u03b5\u03af\u03bd\u03b1\u03b9 \u03bc\u03b9\u03b1 \u03b1\u03ba\u03bf\u03bb\u03bf\u03c5\u03b8\u03af\u03b1 \u03c3\u03c4\u03b7\u03bd \u03bf\u03c0\u03bf\u03af\u03b1 \u03b7 \u03c3\u03b5\u03b9\u03c1\u03ac \u03c4\u03c9\u03bd \u03c0\u03b1\u03c1\u03b1\u03c4\u03b7\u03c1\u03ae\u03c3\u03b5\u03c9\u03bd \u03ad\u03c7\u03b5\u03b9 \u03bd\u03cc\u03b7\u03bc\u03b1. \u0388\u03bd\u03b1 ECG, \u03ad\u03bd\u03b1 \u03b7\u03c7\u03b7\u03c4\u03b9\u03ba\u03cc \u03c3\u03ae\u03bc\u03b1, \u03bf\u03b9 \u03bc\u03b5\u03c4\u03c1\u03ae\u03c3\u03b5\u03b9\u03c2 \u03b1\u03b9\u03c3\u03b8\u03b7\u03c4\u03ae\u03c1\u03c9\u03bd \u03ae \u03bf\u03b9 \u03b5\u03c1\u03b3\u03b1\u03c3\u03c4\u03b7\u03c1\u03b9\u03b1\u03ba\u03ad\u03c2 \u03c4\u03b9\u03bc\u03ad\u03c2 \u03b1\u03c3\u03b8\u03b5\u03bd\u03ce\u03bd \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03b1\u03bd\u03b5\u03be\u03ac\u03c1\u03c4\u03b7\u03c4\u03b5\u03c2 \u03b3\u03c1\u03b1\u03bc\u03bc\u03ad\u03c2 \u03b5\u03bd\u03cc\u03c2 spreadsheet. \u0397 \u03c0\u03bb\u03b7\u03c1\u03bf\u03c6\u03bf\u03c1\u03af\u03b1 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b2\u03c1\u03af\u03c3\u03ba\u03b5\u03c4\u03b1\u03b9 \u03c3\u03c4\u03b7 \u03b4\u03b9\u03ac\u03c1\u03ba\u03b5\u03b9\u03b1 \u03b5\u03bd\u03cc\u03c2 \u03bc\u03bf\u03c4\u03af\u03b2\u03bf\u03c5, \u03c3\u03c4\u03b7 \u03c3\u03c7\u03ad\u03c3\u03b7 \u03bc\u03b1\u03ba\u03c1\u03b9\u03bd\u03ce\u03bd \u03c7\u03c1\u03bf\u03bd\u03b9\u03ba\u03ce\u03bd \u03c3\u03c4\u03b9\u03b3\u03bc\u03ce\u03bd, \u03c3\u03c4\u03b7 \u03c3\u03c5\u03bd\u03c4\u03bf\u03bd\u03b9\u03c3\u03bc\u03ad\u03bd\u03b7 \u03ba\u03af\u03bd\u03b7\u03c3\u03b7 \u03c0\u03bf\u03bb\u03bb\u03ce\u03bd \u03ba\u03b1\u03bd\u03b1\u03bb\u03b9\u03ce\u03bd \u03ae \u03c3\u03c4\u03b7 \u03c3\u03c5\u03c7\u03bd\u03cc\u03c4\u03b7\u03c4\u03b1 \u03b5\u03bd\u03cc\u03c2 \u03c3\u03ae\u03bc\u03b1\u03c4\u03bf\u03c2.<\/p>\n<p>\u0391\u03c5\u03c4\u03cc \u03b4\u03b7\u03bc\u03b9\u03bf\u03c5\u03c1\u03b3\u03b5\u03af \u03c0\u03c1\u03cc\u03b2\u03bb\u03b7\u03bc\u03b1 \u03cc\u03c4\u03b1\u03bd \u03bc\u03ad\u03b8\u03bf\u03b4\u03bf\u03b9 \u03b5\u03be\u03ae\u03b3\u03b7\u03c3\u03b7\u03c2 \u03c0\u03bf\u03c5 \u03b1\u03bd\u03b1\u03c0\u03c4\u03cd\u03c7\u03b8\u03b7\u03ba\u03b1\u03bd \u03b3\u03b9\u03b1 \u03b5\u03b9\u03ba\u03cc\u03bd\u03b5\u03c2 \u03ae \u03b3\u03b5\u03bd\u03b9\u03ba\u03ac tabular \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03b1 \u03b5\u03c6\u03b1\u03c1\u03bc\u03cc\u03b6\u03bf\u03bd\u03c4\u03b1\u03b9 \u03c7\u03c9\u03c1\u03af\u03c2 \u03b5\u03b9\u03b4\u03b9\u03ba\u03ae \u03c0\u03c1\u03bf\u03c3\u03b1\u03c1\u03bc\u03bf\u03b3\u03ae. \u0388\u03bd\u03b1 heatmap \u03c0\u03ac\u03bd\u03c9 \u03c3\u03b5 \u03bc\u03b9\u03b1 \u03ba\u03b1\u03bc\u03c0\u03cd\u03bb\u03b7 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b4\u03b5\u03af\u03c7\u03bd\u03b5\u03b9 \u03c0\u03bf\u03cd \u03b1\u03c0\u03ad\u03b4\u03c9\u03c3\u03b5 relevance \u03bc\u03b9\u03b1 \u03bc\u03ad\u03b8\u03bf\u03b4\u03bf\u03c2, \u03b1\u03bb\u03bb\u03ac \u03b4\u03b5\u03bd \u03b1\u03c0\u03bf\u03b4\u03b5\u03b9\u03ba\u03bd\u03cd\u03b5\u03b9 \u03cc\u03c4\u03b9 \u03ba\u03b1\u03c4\u03b1\u03bd\u03cc\u03b7\u03c3\u03b5 \u03c7\u03c1\u03bf\u03bd\u03b9\u03ba\u03ad\u03c2 \u03b5\u03be\u03b1\u03c1\u03c4\u03ae\u03c3\u03b5\u03b9\u03c2. \u03a3\u03b5 \u03c0\u03bf\u03bb\u03c5\u03ba\u03b1\u03bd\u03b1\u03bb\u03b9\u03ba\u03ac \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03b1, \u03cc\u03c0\u03c9\u03c2 \u03c4\u03b1 \u03b4\u03ce\u03b4\u03b5\u03ba\u03b1 leads \u03b5\u03bd\u03cc\u03c2 ECG, \u03c4\u03bf \u03c3\u03b7\u03bc\u03b1\u03bd\u03c4\u03b9\u03ba\u03cc \u03bc\u03bf\u03c4\u03af\u03b2\u03bf \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03c0\u03c1\u03bf\u03ba\u03cd\u03c0\u03c4\u03b5\u03b9 \u03b1\u03c0\u03cc \u03c3\u03cd\u03b3\u03c7\u03c1\u03bf\u03bd\u03b5\u03c2 \u03ae \u03b1\u03c3\u03cd\u03b3\u03c7\u03c1\u03bf\u03bd\u03b5\u03c2 \u03c3\u03c7\u03ad\u03c3\u03b5\u03b9\u03c2 \u03bc\u03b5\u03c4\u03b1\u03be\u03cd \u03ba\u03b1\u03bd\u03b1\u03bb\u03b9\u03ce\u03bd.<\/p>\n<p>\u03a4\u03bf \u03af\u03b4\u03b9\u03bf \u03b6\u03ae\u03c4\u03b7\u03bc\u03b1 \u03b5\u03bc\u03c6\u03b1\u03bd\u03af\u03b6\u03b5\u03c4\u03b1\u03b9 \u03c0\u03ad\u03c1\u03b1 \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03c5\u03b3\u03b5\u03af\u03b1. Forecasting \u03b6\u03ae\u03c4\u03b7\u03c3\u03b7\u03c2, predictive maintenance, anomaly detection, churn signals \u03ba\u03b1\u03b9 customer-behavior sequences \u03b2\u03b1\u03c3\u03af\u03b6\u03bf\u03bd\u03c4\u03b1\u03b9 \u03c3\u03b5 \u03c7\u03c1\u03bf\u03bd\u03b9\u03ba\u03ae \u03b4\u03bf\u03bc\u03ae. \u0397 <a href=\"https:\/\/twodots.gr\/erminefsimi-multimodal-ai-decision-trees\/\">\u03b5\u03c1\u03bc\u03b7\u03bd\u03b5\u03cd\u03c3\u03b9\u03bc\u03b7 multimodal AI<\/a> \u03b4\u03b5\u03af\u03c7\u03bd\u03b5\u03b9 \u03ae\u03b4\u03b7 \u03cc\u03c4\u03b9 \u03c4\u03bf \u03bc\u03ad\u03c3\u03bf \u03c4\u03b7\u03c2 \u03c0\u03bb\u03b7\u03c1\u03bf\u03c6\u03bf\u03c1\u03af\u03b1\u03c2 \u03b1\u03bb\u03bb\u03ac\u03b6\u03b5\u03b9 \u03ba\u03b1\u03b9 \u03c4\u03bf \u03b5\u03af\u03b4\u03bf\u03c2 \u03c4\u03b7\u03c2 \u03b5\u03be\u03ae\u03b3\u03b7\u03c3\u03b7\u03c2\u00b7 \u03c3\u03c4\u03b9\u03c2 \u03c7\u03c1\u03bf\u03bd\u03bf\u03c3\u03b5\u03b9\u03c1\u03ad\u03c2 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03c0\u03c1\u03bf\u03c3\u03c4\u03b5\u03b8\u03bf\u03cd\u03bd \u03bf \u03c7\u03c1\u03cc\u03bd\u03bf\u03c2, \u03b7 \u03c3\u03c5\u03c7\u03bd\u03cc\u03c4\u03b7\u03c4\u03b1 \u03ba\u03b1\u03b9 \u03bf\u03b9 \u03c3\u03c7\u03ad\u03c3\u03b5\u03b9\u03c2 \u03bc\u03b5\u03c4\u03b1\u03be\u03cd \u03ba\u03b1\u03bd\u03b1\u03bb\u03b9\u03ce\u03bd.<\/p>\n<aside class=\"td-article-note\"><strong>\u03a4\u03b5\u03c7\u03bd\u03b9\u03ba\u03ac \u03c3\u03c5\u03bc\u03b2\u03b1\u03c4\u03cc \u03b4\u03b5\u03bd \u03c3\u03b7\u03bc\u03b1\u03af\u03bd\u03b5\u03b9 time-series-aware:<\/strong> \u03bc\u03b9\u03b1 \u03b2\u03b9\u03b2\u03bb\u03b9\u03bf\u03b8\u03ae\u03ba\u03b7 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b4\u03ad\u03c7\u03b5\u03c4\u03b1\u03b9 tensor \u03c7\u03c1\u03bf\u03bd\u03b9\u03ba\u03ce\u03bd \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd \u03c7\u03c9\u03c1\u03af\u03c2 \u03b7 \u03bc\u03ad\u03b8\u03bf\u03b4\u03bf\u03c2 \u03ae \u03c4\u03bf metric \u03bd\u03b1 \u03ad\u03c7\u03b5\u03b9 \u03c3\u03c7\u03b5\u03b4\u03b9\u03b1\u03c3\u03c4\u03b5\u03af \u03ba\u03b1\u03b9 \u03b5\u03c0\u03b9\u03ba\u03c5\u03c1\u03c9\u03b8\u03b5\u03af \u03b3\u03b9\u03b1 temporal dependencies, cross-channel interactions \u03ae frequency-domain patterns.<\/aside>\n<h2 id=\"exi-xai-frameworks\">\u03a0\u03ce\u03c2 \u03b5\u03bd\u03c4\u03bf\u03c0\u03af\u03c3\u03c4\u03b7\u03ba\u03b1\u03bd \u03c4\u03b1 \u03ad\u03be\u03b9 XAI frameworks<\/h2>\n<p>\u0397 \u03b5\u03c1\u03b3\u03b1\u03c3\u03af\u03b1 <em>Software Frameworks for Explainable AI in Time Series Classification: A Systematic Review<\/em>, arXiv 2608.21449 v1, \u03b5\u03be\u03ad\u03c4\u03b1\u03c3\u03b5 software frameworks \u03c0\u03bf\u03c5 \u03c0\u03b1\u03c1\u03ac\u03b3\u03bf\u03c5\u03bd \u03ae \u03b1\u03be\u03b9\u03bf\u03bb\u03bf\u03b3\u03bf\u03cd\u03bd \u03b5\u03be\u03b7\u03b3\u03ae\u03c3\u03b5\u03b9\u03c2 \u03b3\u03b9\u03b1 time-series classification. \u039f\u03b9 \u03b5\u03c1\u03b5\u03c5\u03bd\u03b7\u03c4\u03ad\u03c2 \u03ad\u03ba\u03b1\u03bd\u03b1\u03bd \u03b1\u03bd\u03b1\u03b6\u03ae\u03c4\u03b7\u03c3\u03b7 \u03c3\u03c4\u03bf GitHub \u03c3\u03c4\u03b9\u03c2 5 \u0394\u03b5\u03ba\u03b5\u03bc\u03b2\u03c1\u03af\u03bf\u03c5 2025 \u03bc\u03b5 \u03c0\u03ad\u03bd\u03c4\u03b5 \u03c3\u03c5\u03bd\u03b4\u03c5\u03b1\u03c3\u03bc\u03bf\u03cd\u03c2 \u03cc\u03c1\u03c9\u03bd \u03b3\u03cd\u03c1\u03c9 \u03b1\u03c0\u03cc explainable AI, evaluation \u03ba\u03b1\u03b9 time series.<\/p>\n<p>\u0397 \u03b1\u03c1\u03c7\u03b9\u03ba\u03ae \u03b1\u03bd\u03b1\u03b6\u03ae\u03c4\u03b7\u03c3\u03b7 \u03b5\u03c0\u03ad\u03c3\u03c4\u03c1\u03b5\u03c8\u03b5 750 \u03b1\u03c0\u03bf\u03c4\u03b5\u03bb\u03ad\u03c3\u03bc\u03b1\u03c4\u03b1. \u039c\u03b5\u03c4\u03ac \u03c4\u03b7\u03bd \u03b1\u03c6\u03b1\u03af\u03c1\u03b5\u03c3\u03b7 \u03b4\u03b9\u03c0\u03bb\u03bf\u03c4\u03cd\u03c0\u03c9\u03bd \u03ad\u03bc\u03b5\u03b9\u03bd\u03b1\u03bd 589 repositories \u03ba\u03b1\u03b9, \u03ad\u03c0\u03b5\u03b9\u03c4\u03b1 \u03b1\u03c0\u03cc \u03c6\u03af\u03bb\u03c4\u03c1\u03bf \u03b5\u03bb\u03ac\u03c7\u03b9\u03c3\u03c4\u03b7\u03c2 \u03b4\u03c1\u03b1\u03c3\u03c4\u03b7\u03c1\u03b9\u03cc\u03c4\u03b7\u03c4\u03b1\u03c2 \u03ba\u03b1\u03b9 \u03ba\u03bf\u03b9\u03bd\u03cc\u03c4\u03b7\u03c4\u03b1\u03c2, 115. \u0391\u03ba\u03bf\u03bb\u03bf\u03cd\u03b8\u03b7\u03c3\u03b5 \u03c7\u03b5\u03b9\u03c1\u03bf\u03ba\u03af\u03bd\u03b7\u03c4\u03bf\u03c2 \u03ad\u03bb\u03b5\u03b3\u03c7\u03bf\u03c2: \u03c4\u03bf framework \u03ad\u03c0\u03c1\u03b5\u03c0\u03b5 \u03bd\u03b1 \u03b4\u03b7\u03bb\u03ce\u03bd\u03b5\u03b9 \u03c5\u03c0\u03bf\u03c3\u03c4\u03ae\u03c1\u03b9\u03be\u03b7 \u03c7\u03c1\u03bf\u03bd\u03bf\u03c3\u03b5\u03b9\u03c1\u03ce\u03bd, \u03bd\u03b1 \u03c0\u03c1\u03bf\u03c3\u03c6\u03ad\u03c1\u03b5\u03b9 \u03b5\u03c0\u03b1\u03c1\u03ba\u03ad\u03c2 \u03b5\u03cd\u03c1\u03bf\u03c2 \u03bc\u03b5\u03b8\u03cc\u03b4\u03c9\u03bd \u03ae metrics, \u03bd\u03b1 \u03b5\u03b3\u03ba\u03b1\u03b8\u03af\u03c3\u03c4\u03b1\u03c4\u03b1\u03b9 \u03c9\u03c2 Python package \u03ba\u03b1\u03b9 \u03bd\u03b1 \u03ad\u03c7\u03b5\u03b9 \u03c3\u03c7\u03b5\u03c4\u03b9\u03ba\u03ae \u03b4\u03b7\u03bc\u03bf\u03c3\u03af\u03b5\u03c5\u03c3\u03b7 \u03ae \u03b5\u03c0\u03b1\u03c1\u03ba\u03ae \u03c4\u03b5\u03ba\u03bc\u03b7\u03c1\u03af\u03c9\u03c3\u03b7.<\/p>\n<p>\u0397 \u03b4\u03b9\u03b1\u03b4\u03b9\u03ba\u03b1\u03c3\u03af\u03b1 \u03ba\u03b1\u03c4\u03ad\u03bb\u03b7\u03be\u03b5 \u03c3\u03b5 \u03ad\u03be\u03b9 frameworks: TSInterpret, tsCaptum, SIGN-XAI-2, Quantus, time_interpret \u03ba\u03b1\u03b9 XTSC-Bench. \u0397 \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ae \u03b5\u03af\u03bd\u03b1\u03b9 \u03c7\u03c1\u03ae\u03c3\u03b9\u03bc\u03b7 \u03b1\u03bb\u03bb\u03ac \u03cc\u03c7\u03b9 \u03b5\u03be\u03b1\u03bd\u03c4\u03bb\u03b7\u03c4\u03b9\u03ba\u03ae. \u0397 \u03b1\u03bd\u03b1\u03b6\u03ae\u03c4\u03b7\u03c3\u03b7 \u03ad\u03b3\u03b9\u03bd\u03b5 \u03b1\u03c0\u03bf\u03ba\u03bb\u03b5\u03b9\u03c3\u03c4\u03b9\u03ba\u03ac \u03c3\u03c4\u03bf GitHub, \u03ac\u03c1\u03b1 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03bb\u03b5\u03af\u03c0\u03b5\u03b9 software \u03c0\u03bf\u03c5 \u03b4\u03b7\u03bc\u03bf\u03c3\u03b9\u03b5\u03cd\u03c4\u03b7\u03ba\u03b5 \u03ae \u03c3\u03c5\u03bd\u03c4\u03b7\u03c1\u03b5\u03af\u03c4\u03b1\u03b9 \u03b1\u03bb\u03bb\u03bf\u03cd. Stars \u03ba\u03b1\u03b9 forks \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03ae\u03b8\u03b7\u03ba\u03b1\u03bd \u03c9\u03c2 \u03c6\u03af\u03bb\u03c4\u03c1\u03bf \u03ba\u03bf\u03b9\u03bd\u03cc\u03c4\u03b7\u03c4\u03b1\u03c2 \u03ba\u03b1\u03b9 \u03c3\u03c5\u03bd\u03c4\u03ae\u03c1\u03b7\u03c3\u03b7\u03c2, \u03cc\u03c7\u03b9 \u03c9\u03c2 \u03b1\u03c0\u03cc\u03b4\u03b5\u03b9\u03be\u03b7 \u03b5\u03c0\u03b9\u03c3\u03c4\u03b7\u03bc\u03bf\u03bd\u03b9\u03ba\u03ae\u03c2 \u03c0\u03bf\u03b9\u03cc\u03c4\u03b7\u03c4\u03b1\u03c2.<\/p>\n<div class=\"td-chart td-chart--metrics\">\n<div class=\"td-chart-head\">\n<p class=\"td-chart-kicker\">\u03a4\u03b5\u03ba\u03bc\u03b7\u03c1\u03b9\u03c9\u03bc\u03ad\u03bd\u03b7 \u03b5\u03b9\u03ba\u03cc\u03bd\u03b1<\/p>\n<p class=\"td-chart-title\">\u03a4\u03ad\u03c3\u03c3\u03b5\u03c1\u03b9\u03c2 \u03b1\u03c1\u03b9\u03b8\u03bc\u03bf\u03af \u03c0\u03bf\u03c5 \u03bf\u03c1\u03af\u03b6\u03bf\u03c5\u03bd \u03c4\u03bf \u03c3\u03b7\u03bc\u03b5\u03c1\u03b9\u03bd\u03cc XAI \u03bf\u03b9\u03ba\u03bf\u03c3\u03cd\u03c3\u03c4\u03b7\u03bc\u03b1<\/p>\n<p class=\"td-chart-intro\">\u039f\u03b9 \u03c4\u03b9\u03bc\u03ad\u03c2 \u03c0\u03c1\u03bf\u03ad\u03c1\u03c7\u03bf\u03bd\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc \u03c4\u03b7 \u03c3\u03c5\u03c3\u03c4\u03b7\u03bc\u03b1\u03c4\u03b9\u03ba\u03ae \u03b1\u03bd\u03b1\u03c3\u03ba\u03cc\u03c0\u03b7\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03c4\u03bf \u03c0\u03b5\u03af\u03c1\u03b1\u03bc\u03b1 \u03b1\u03bd\u03b1\u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03b9\u03bc\u03cc\u03c4\u03b7\u03c4\u03b1\u03c2 \u03c4\u03b7\u03c2 \u03af\u03b4\u03b9\u03b1\u03c2 \u03b5\u03c1\u03b3\u03b1\u03c3\u03af\u03b1\u03c2.<\/p>\n<\/div>\n<div class=\"td-metric-grid\">\n<div class=\"td-metric-card\"><span class=\"td-metric-value\">6<\/span><span class=\"td-metric-label\">frameworks \u03bc\u03b5 \u03c1\u03b7\u03c4\u03ae \u03c5\u03c0\u03bf\u03c3\u03c4\u03ae\u03c1\u03b9\u03be\u03b7 \u03c7\u03c1\u03bf\u03bd\u03bf\u03c3\u03b5\u03b9\u03c1\u03ce\u03bd<\/span><\/div>\n<div class=\"td-metric-card\"><span class=\"td-metric-value\">16 \/ 51<\/span><span class=\"td-metric-label\">\u03bc\u03ad\u03b8\u03bf\u03b4\u03bf\u03b9 \u03c3\u03c7\u03b5\u03b4\u03b9\u03b1\u03c3\u03bc\u03ad\u03bd\u03b5\u03c2 \u03b5\u03b9\u03b4\u03b9\u03ba\u03ac \u03b3\u03b9\u03b1 time series<\/span><\/div>\n<div class=\"td-metric-card\"><span class=\"td-metric-value\">2 \/ 52<\/span><span class=\"td-metric-label\">metrics \u03c3\u03c7\u03b5\u03b4\u03b9\u03b1\u03c3\u03bc\u03ad\u03bd\u03b1 \u03b5\u03b9\u03b4\u03b9\u03ba\u03ac \u03b3\u03b9\u03b1 time series<\/span><\/div>\n<div class=\"td-metric-card\"><span class=\"td-metric-value\">0 \/ 443<\/span><span class=\"td-metric-label\">ECG \u03b5\u03be\u03b7\u03b3\u03ae\u03c3\u03b5\u03b9\u03c2 \u03bc\u03b5 Spearman rho \u03c0\u03ac\u03bd\u03c9 \u03b1\u03c0\u03cc 0,5 \u03bc\u03b5\u03c4\u03b1\u03be\u03cd \u03c4\u03c9\u03bd \u03b4\u03cd\u03bf IG implementations<\/span><\/div>\n<\/div>\n<p class=\"td-chart-source\">\u03a0\u03b7\u03b3\u03ae: arXiv 2608.21449 v1, \u03b5\u03bd\u03cc\u03c4\u03b7\u03c4\u03b5\u03c2 3.1\u20133.5.<\/p>\n<\/div>\n<h2 id=\"ti-prosferei-kathe-framework\">\u03a4\u03b9 \u03c0\u03c1\u03bf\u03c3\u03c6\u03ad\u03c1\u03b5\u03b9 \u03ba\u03ac\u03b8\u03b5 framework \u03c3\u03c4\u03b7\u03bd \u03c0\u03c1\u03ac\u03be\u03b7<\/h2>\n<p>\u03a4\u03c1\u03af\u03b1 frameworks \u03c3\u03c5\u03bd\u03b4\u03c5\u03ac\u03b6\u03bf\u03c5\u03bd \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae \u03b5\u03be\u03b7\u03b3\u03ae\u03c3\u03b5\u03c9\u03bd \u03ba\u03b1\u03b9 \u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7: time_interpret, Quantus \u03ba\u03b1\u03b9 XTSC-Bench. \u03a4\u03b1 TSInterpret, tsCaptum \u03ba\u03b1\u03b9 SIGN-XAI-2 \u03b5\u03c0\u03b9\u03ba\u03b5\u03bd\u03c4\u03c1\u03ce\u03bd\u03bf\u03bd\u03c4\u03b1\u03b9 \u03c3\u03c4\u03b9\u03c2 \u03bc\u03b5\u03b8\u03cc\u03b4\u03bf\u03c5\u03c2 \u03b5\u03be\u03ae\u03b3\u03b7\u03c3\u03b7\u03c2. \u039a\u03b1\u03b9 \u03c4\u03b1 \u03ad\u03be\u03b9 \u03c5\u03c0\u03bf\u03c3\u03c4\u03b7\u03c1\u03af\u03b6\u03bf\u03c5\u03bd PyTorch. \u03a4\u03bf TSInterpret \u03ad\u03c7\u03b5\u03b9 \u03c4\u03bf \u03b5\u03c5\u03c1\u03cd\u03c4\u03b5\u03c1\u03bf backend coverage, \u03bc\u03b5 PyTorch, scikit-learn \u03ba\u03b1\u03b9 TensorFlow, \u03b5\u03bd\u03ce \u03c4\u03bf XTSC-Bench \u03ba\u03bb\u03b7\u03c1\u03bf\u03bd\u03bf\u03bc\u03b5\u03af \u03b1\u03c5\u03c4\u03ac \u03c4\u03b1 backends \u03b5\u03c0\u03b5\u03b9\u03b4\u03ae \u03b2\u03b1\u03c3\u03af\u03b6\u03b5\u03c4\u03b1\u03b9 \u03c3\u03c4\u03bf TSInterpret.<\/p>\n<p>\u0397 \u03b1\u03c1\u03b9\u03b8\u03bc\u03b7\u03c4\u03b9\u03ba\u03ae \u03c5\u03c0\u03b5\u03c1\u03bf\u03c7\u03ae \u03b4\u03b5\u03bd \u03b9\u03c3\u03bf\u03b4\u03c5\u03bd\u03b1\u03bc\u03b5\u03af \u03bc\u03b5 \u03ba\u03b1\u03c4\u03b1\u03bb\u03bb\u03b7\u03bb\u03cc\u03c4\u03b7\u03c4\u03b1. \u03a4\u03bf Quantus \u03ad\u03c7\u03b5\u03b9 \u03c4\u03b7 \u03bc\u03b5\u03b3\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03b7 \u03c3\u03c5\u03bb\u03bb\u03bf\u03b3\u03ae \u03c4\u03b7\u03c2 \u03b1\u03bd\u03b1\u03c3\u03ba\u03cc\u03c0\u03b7\u03c3\u03b7\u03c2, \u03bc\u03b5 26 wrapped XAI methods \u03ba\u03b1\u03b9 36 metrics, \u03b1\u03bb\u03bb\u03ac \u03ba\u03b1\u03bc\u03af\u03b1 \u03b1\u03c0\u03cc \u03c4\u03b9\u03c2 \u03bc\u03b5\u03b8\u03cc\u03b4\u03bf\u03c5\u03c2 \u03c4\u03bf\u03c5 \u03b4\u03b5\u03bd \u03b5\u03af\u03c7\u03b5 \u03b1\u03bd\u03b1\u03c0\u03c4\u03c5\u03c7\u03b8\u03b5\u03af \u03b5\u03b9\u03b4\u03b9\u03ba\u03ac \u03b3\u03b9\u03b1 \u03c7\u03c1\u03bf\u03bd\u03bf\u03c3\u03b5\u03b9\u03c1\u03ad\u03c2. \u03a4\u03bf time_interpret \u03c0\u03c1\u03bf\u03c3\u03c6\u03ad\u03c1\u03b5\u03b9 \u03c4\u03bf \u03bc\u03b5\u03b3\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03bf \u03c3\u03cd\u03bd\u03bf\u03bb\u03bf time-series-specific \u03bc\u03b5\u03b8\u03cc\u03b4\u03c9\u03bd: \u03b5\u03bd\u03bd\u03ad\u03b1, \u03cc\u03bb\u03b5\u03c2 \u03bc\u03b5 \u03c5\u03c0\u03bf\u03c3\u03c4\u03ae\u03c1\u03b9\u03be\u03b7 multivariate time series, \u03bc\u03b1\u03b6\u03af \u03bc\u03b5 \u03c4\u03b1 \u03b4\u03cd\u03bf \u03b5\u03b9\u03b4\u03b9\u03ba\u03ac metrics.<\/p>\n<div class=\"td-comparison td-comparison-cards td-comparison-cards--horizontal\">\n<div class=\"td-comparison-grid td-comparison-grid-three\">\n<div class=\"td-platform-card\">\n<p class=\"td-comparison-title\">\u03a0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae \u03b5\u03be\u03b7\u03b3\u03ae\u03c3\u03b5\u03c9\u03bd<\/p>\n<p>TSInterpret, tsCaptum \u03ba\u03b1\u03b9 SIGN-XAI-2 \u03b5\u03c3\u03c4\u03b9\u03ac\u03b6\u03bf\u03c5\u03bd \u03c3\u03c4\u03b7\u03bd \u03b5\u03c6\u03b1\u03c1\u03bc\u03bf\u03b3\u03ae XAI methods. \u039c\u03cc\u03bd\u03bf \u03c4\u03bf SIGN-XAI-2 \u03c0\u03b5\u03c1\u03b9\u03bb\u03b1\u03bc\u03b2\u03ac\u03bd\u03b5\u03b9 frequency-aware \u03bc\u03ad\u03b8\u03bf\u03b4\u03bf \u03c3\u03c4\u03b7\u03bd \u03b1\u03bd\u03b1\u03c3\u03ba\u03cc\u03c0\u03b7\u03c3\u03b7.<\/p>\n<div class=\"td-badge-row\"><span class=\"td-badge\">Methods<\/span><span class=\"td-badge\">Implementation matters<\/span><\/div>\n<\/div>\n<div class=\"td-platform-card\">\n<p class=\"td-comparison-title\">\u03a0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae \u03ba\u03b1\u03b9 evaluation<\/p>\n<p>time_interpret \u03ba\u03b1\u03b9 Quantus \u03c3\u03c5\u03bd\u03b4\u03c5\u03ac\u03b6\u03bf\u03c5\u03bd explainers \u03bc\u03b5 metrics. \u03a4\u03bf \u03c0\u03c1\u03ce\u03c4\u03bf \u03ad\u03c7\u03b5\u03b9 \u03b5\u03bd\u03bd\u03ad\u03b1 time-series-specific methods \u03ba\u03b1\u03b9 \u03b4\u03cd\u03bf \u03b5\u03b9\u03b4\u03b9\u03ba\u03ac metrics\u00b7 \u03c4\u03bf \u03b4\u03b5\u03cd\u03c4\u03b5\u03c1\u03bf \u03ad\u03c7\u03b5\u03b9 \u03bc\u03b5\u03b3\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03bf \u03b3\u03b5\u03bd\u03b9\u03ba\u03cc \u03b5\u03cd\u03c1\u03bf\u03c2.<\/p>\n<div class=\"td-badge-row\"><span class=\"td-badge\">Metrics<\/span><span class=\"td-badge\">Scope check<\/span><\/div>\n<\/div>\n<div class=\"td-platform-card td-platform-card--navy\">\n<p class=\"td-comparison-title\">Benchmarking<\/p>\n<p>\u03a4\u03bf XTSC-Bench \u03c7\u03c4\u03af\u03b6\u03b5\u03b9 \u03c0\u03ac\u03bd\u03c9 \u03c3\u03b5 TSInterpret \u03ba\u03b1\u03b9 Quantus \u03ba\u03b1\u03b9 \u03c0\u03b1\u03c1\u03ad\u03c7\u03b5\u03b9 synthetic datasets \u03bc\u03b5 ground truth \u03bc\u03b1\u03b6\u03af \u03bc\u03b5 \u03c0\u03c1\u03cc\u03c3\u03b2\u03b1\u03c3\u03b7 \u03c3\u03c4\u03b1 UCR \u03ba\u03b1\u03b9 UEA archives.<\/p>\n<div class=\"td-badge-row\"><span class=\"td-badge\">Datasets<\/span><span class=\"td-badge\">Ground truth limits<\/span><\/div>\n<\/div>\n<\/div>\n<\/div>\n<p>\u0393\u03b9\u03b1 \u03bc\u03b9\u03b1 \u03bf\u03bc\u03ac\u03b4\u03b1 \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ae\u03c2 \u03b5\u03c1\u03b3\u03b1\u03bb\u03b5\u03af\u03bf\u03c5, \u03b7 \u03c3\u03c9\u03c3\u03c4\u03ae \u03b5\u03c1\u03ce\u03c4\u03b7\u03c3\u03b7 \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u00ab\u03c0\u03bf\u03b9\u03bf framework \u03ad\u03c7\u03b5\u03b9 \u03c4\u03b1 \u03c0\u03b5\u03c1\u03b9\u03c3\u03c3\u03cc\u03c4\u03b5\u03c1\u03b1;\u00bb. \u0395\u03af\u03bd\u03b1\u03b9 \u00ab\u03c0\u03bf\u03b9\u03bf \u03ba\u03b1\u03bb\u03cd\u03c0\u03c4\u03b5\u03b9 \u03c4\u03b9\u03c2 \u03b9\u03b4\u03b9\u03cc\u03c4\u03b7\u03c4\u03b5\u03c2 \u03c4\u03bf\u03c5 \u03b4\u03b9\u03ba\u03bf\u03cd \u03bc\u03b1\u03c2 \u03c3\u03ae\u03bc\u03b1\u03c4\u03bf\u03c2, \u03c0\u03bf\u03b9\u03b1 \u03b1\u03ba\u03c1\u03b9\u03b2\u03ce\u03c2 implementation \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03b5\u03af \u03ba\u03b1\u03b9 \u03bc\u03b5 \u03c0\u03bf\u03b9\u03bf\u03bd \u03c4\u03c1\u03cc\u03c0\u03bf \u03b8\u03b1 \u03b5\u03bb\u03ad\u03b3\u03be\u03bf\u03c5\u03bc\u03b5 \u03c4\u03b7\u03bd \u03b5\u03be\u03ae\u03b3\u03b7\u03c3\u03b7;\u00bb. \u0397 \u03af\u03b4\u03b9\u03b1 \u03bb\u03bf\u03b3\u03b9\u03ba\u03ae \u03b9\u03c3\u03c7\u03cd\u03b5\u03b9 \u03ba\u03b1\u03b9 \u03c3\u03b5 \u03ba\u03ac\u03b8\u03b5 \u03c3\u03cd\u03c3\u03c4\u03b7\u03bc\u03b1 <a href=\"https:\/\/twodots.gr\/data-silos-audit-trail-smart-manufacturing\/\">smart manufacturing \u03c0\u03bf\u03c5 \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 audit trail<\/a> \u03b1\u03c0\u03cc \u03b1\u03b9\u03c3\u03b8\u03b7\u03c4\u03ae\u03c1\u03b1 \u03ad\u03c9\u03c2 \u03b5\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03b7\u03c3\u03b9\u03b1\u03ba\u03ae \u03b1\u03c0\u03cc\u03c6\u03b1\u03c3\u03b7.<\/p>\n<h2 id=\"methodoi-xroniki-exeidikefsi\">\u039f\u03b9 51 \u03bc\u03ad\u03b8\u03bf\u03b4\u03bf\u03b9 \u03ba\u03b1\u03b9 \u03c4\u03bf \u03ba\u03b5\u03bd\u03cc \u03c4\u03b7\u03c2 \u03c7\u03c1\u03bf\u03bd\u03b9\u03ba\u03ae\u03c2 \u03b5\u03be\u03b5\u03b9\u03b4\u03af\u03ba\u03b5\u03c5\u03c3\u03b7\u03c2<\/h2>\n<p>\u03a3\u03c5\u03bd\u03bf\u03bb\u03b9\u03ba\u03ac, \u03c4\u03b1 frameworks \u03c0\u03b5\u03c1\u03b9\u03bb\u03b1\u03bc\u03b2\u03ac\u03bd\u03bf\u03c5\u03bd 51 \u03bc\u03b5\u03b8\u03cc\u03b4\u03bf\u03c5\u03c2 XAI: 16 perturbation-based, 25 gradient-based, \u03c4\u03ad\u03c3\u03c3\u03b5\u03c1\u03b9\u03c2 counterfactual \u03ba\u03b1\u03b9 \u03ad\u03be\u03b9 \u03ac\u03bb\u03bb\u03bf\u03c5 \u03c4\u03cd\u03c0\u03bf\u03c5. \u039c\u03cc\u03bd\u03bf 16 \u03b4\u03b7\u03bb\u03ce\u03bd\u03bf\u03c5\u03bd \u03c1\u03b7\u03c4\u03ac \u03cc\u03c4\u03b9 \u03b1\u03bd\u03b1\u03c0\u03c4\u03cd\u03c7\u03b8\u03b7\u03ba\u03b1\u03bd \u03b3\u03b9\u03b1 \u03c7\u03c1\u03bf\u03bd\u03bf\u03c3\u03b5\u03b9\u03c1\u03ad\u03c2. \u03a4\u03bf \u03cc\u03c4\u03b9 \u03bf\u03b9 \u03c5\u03c0\u03cc\u03bb\u03bf\u03b9\u03c0\u03b5\u03c2 \u03bc\u03c0\u03bf\u03c1\u03bf\u03cd\u03bd \u03bd\u03b1 \u03b4\u03b5\u03c7\u03b8\u03bf\u03cd\u03bd \u03ad\u03bd\u03b1\u03bd \u03c7\u03c1\u03bf\u03bd\u03b9\u03ba\u03cc \u03c0\u03af\u03bd\u03b1\u03ba\u03b1 \u03c9\u03c2 input \u03b4\u03b5\u03bd \u03c3\u03b7\u03bc\u03b1\u03af\u03bd\u03b5\u03b9 \u03cc\u03c4\u03b9 \u03bc\u03bf\u03bd\u03c4\u03b5\u03bb\u03bf\u03c0\u03bf\u03b9\u03bf\u03cd\u03bd \u03c3\u03c9\u03c3\u03c4\u03ac \u03c4\u03b7 \u03c7\u03c1\u03bf\u03bd\u03b9\u03ba\u03ae \u03b4\u03bf\u03bc\u03ae.<\/p>\n<p>\u0394\u03cd\u03bf \u03c0\u03c1\u03bf\u03c3\u03b5\u03b3\u03b3\u03af\u03c3\u03b5\u03b9\u03c2 \u03b4\u03b5\u03af\u03c7\u03bd\u03bf\u03c5\u03bd \u03c0\u03ce\u03c2 \u03c0\u03c1\u03bf\u03c3\u03c4\u03af\u03b8\u03b5\u03c4\u03b1\u03b9 \u03c7\u03c1\u03bf\u03bd\u03b9\u03ba\u03ae \u03b5\u03c0\u03af\u03b3\u03bd\u03c9\u03c3\u03b7. \u03a4\u03bf Temporal Saliency Rescaling \u03c5\u03c0\u03bf\u03bb\u03bf\u03b3\u03af\u03b6\u03b5\u03b9 \u03be\u03b5\u03c7\u03c9\u03c1\u03b9\u03c3\u03c4\u03ac relevance \u03b3\u03b9\u03b1 \u03c7\u03c1\u03bf\u03bd\u03b9\u03ba\u03ac \u03c3\u03b7\u03bc\u03b5\u03af\u03b1 \u03ba\u03b1\u03b9 features \u03ba\u03b1\u03b9 \u03c3\u03c5\u03bd\u03b4\u03c5\u03ac\u03b6\u03b5\u03b9 \u03c4\u03b1 \u03b4\u03cd\u03bf. \u03a4\u03bf Time Forward Tunnel \u03c5\u03c0\u03bf\u03bb\u03bf\u03b3\u03af\u03b6\u03b5\u03b9 \u03c4\u03b7 \u03c3\u03b7\u03bc\u03b1\u03c3\u03af\u03b1 \u03ba\u03ac\u03b8\u03b5 \u03c7\u03c1\u03bf\u03bd\u03b9\u03ba\u03ae\u03c2 \u03c3\u03c4\u03b9\u03b3\u03bc\u03ae\u03c2 \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03ce\u03bd\u03c4\u03b1\u03c2 \u03bc\u03cc\u03bd\u03bf \u03c4\u03b1 \u03c0\u03c1\u03bf\u03b7\u03b3\u03bf\u03cd\u03bc\u03b5\u03bd\u03b1 \u03c3\u03b7\u03bc\u03b5\u03af\u03b1, \u03ce\u03c3\u03c4\u03b5 \u03b7 \u03b5\u03be\u03ae\u03b3\u03b7\u03c3\u03b7 \u03bd\u03b1 \u03bc\u03b7 \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03b5\u03af \u03c0\u03bb\u03b7\u03c1\u03bf\u03c6\u03bf\u03c1\u03af\u03b1 \u03b1\u03c0\u03cc \u03c4\u03bf \u03bc\u03ad\u03bb\u03bb\u03bf\u03bd.<\/p>\n<p>\u0393\u03b9\u03b1 forecasting, fraud monitoring \u03ae predictive maintenance, \u03b1\u03c5\u03c4\u03ae \u03b7 \u03b4\u03b9\u03ac\u03ba\u03c1\u03b9\u03c3\u03b7 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b5\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03b7\u03c3\u03b9\u03b1\u03ba\u03ac \u03ba\u03c1\u03af\u03c3\u03b9\u03bc\u03b7. \u0391\u03bd \u03ad\u03bd\u03b1 explanation pipeline \u00ab\u03b2\u03bb\u03ad\u03c0\u03b5\u03b9\u00bb \u03bc\u03b5\u03c4\u03b1\u03b3\u03b5\u03bd\u03ad\u03c3\u03c4\u03b5\u03c1\u03b1 \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03b1 \u03b3\u03b9\u03b1 \u03bd\u03b1 \u03b5\u03be\u03b7\u03b3\u03ae\u03c3\u03b5\u03b9 \u03b1\u03c0\u03cc\u03c6\u03b1\u03c3\u03b7 \u03c0\u03bf\u03c5 \u03c3\u03c4\u03b7\u03bd \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ae \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03af\u03b1 \u03bb\u03b1\u03bc\u03b2\u03ac\u03bd\u03b5\u03c4\u03b1\u03b9 \u03c3\u03b5 real time, \u03b7 \u03b5\u03be\u03ae\u03b3\u03b7\u03c3\u03b7 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c0\u03b1\u03c1\u03b1\u03c0\u03bb\u03b1\u03bd\u03b7\u03c4\u03b9\u03ba\u03ae \u03b1\u03ba\u03cc\u03bc\u03b7 \u03ba\u03b1\u03b9 \u03b1\u03bd \u03bf \u03ba\u03ce\u03b4\u03b9\u03ba\u03b1\u03c2 \u03b5\u03ba\u03c4\u03b5\u03bb\u03b5\u03af\u03c4\u03b1\u03b9 \u03c7\u03c9\u03c1\u03af\u03c2 \u03c3\u03c6\u03ac\u03bb\u03bc\u03b1.<\/p>\n<p>\u0397 \u03c7\u03c1\u03bf\u03bd\u03b9\u03ba\u03ae \u03b5\u03be\u03b5\u03b9\u03b4\u03af\u03ba\u03b5\u03c5\u03c3\u03b7 \u03b4\u03b5\u03bd \u03b1\u03ba\u03c5\u03c1\u03ce\u03bd\u03b5\u03b9 \u03c4\u03b1 \u03b3\u03b5\u03bd\u03b9\u03ba\u03ac explainers. \u03a4\u03bf\u03c5\u03c2 \u03c4\u03bf\u03c0\u03bf\u03b8\u03b5\u03c4\u03b5\u03af \u03c3\u03c4\u03bf \u03c3\u03c9\u03c3\u03c4\u03cc \u03b5\u03c0\u03af\u03c0\u03b5\u03b4\u03bf \u03c4\u03b5\u03ba\u03bc\u03b7\u03c1\u03af\u03c9\u03c3\u03b7\u03c2. \u039c\u03b9\u03b1 \u03bf\u03bc\u03ac\u03b4\u03b1 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03b5\u03b9 saliency, occlusion \u03ae Integrated Gradients \u03c9\u03c2 \u03b1\u03c1\u03c7\u03b9\u03ba\u03cc \u03c6\u03b1\u03ba\u03cc, \u03b1\u03bb\u03bb\u03ac \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b1\u03c0\u03bf\u03b4\u03b5\u03af\u03be\u03b5\u03b9 \u03cc\u03c4\u03b9 preprocessing, baseline, windowing \u03ba\u03b1\u03b9 sampling \u03b4\u03b5\u03bd \u03b5\u03b9\u03c3\u03ac\u03b3\u03bf\u03c5\u03bd \u03c0\u03bb\u03b7\u03c1\u03bf\u03c6\u03bf\u03c1\u03af\u03b1 \u03c0\u03bf\u03c5 \u03b4\u03b5\u03bd \u03c5\u03c0\u03ae\u03c1\u03c7\u03b5 \u03c4\u03b7 \u03c3\u03c4\u03b9\u03b3\u03bc\u03ae \u03c4\u03b7\u03c2 \u03c0\u03c1\u03cc\u03b2\u03bb\u03b5\u03c8\u03b7\u03c2.<\/p>\n<h2 id=\"syxnotites-dft-lrp\">\u03a4\u03bf \u03c3\u03c7\u03b5\u03b4\u03cc\u03bd \u03ac\u03b4\u03b5\u03b9\u03bf \u03c0\u03b5\u03b4\u03af\u03bf \u03c4\u03c9\u03bd \u03c3\u03c5\u03c7\u03bd\u03bf\u03c4\u03ae\u03c4\u03c9\u03bd<\/h2>\n<p>\u0391\u03c0\u03cc \u03c4\u03b9\u03c2 \u03bc\u03b5\u03b8\u03cc\u03b4\u03bf\u03c5\u03c2 \u03c0\u03bf\u03c5 \u03b5\u03be\u03b5\u03c4\u03ac\u03c3\u03c4\u03b7\u03ba\u03b1\u03bd, \u03bc\u03cc\u03bd\u03bf \u03b7 DFT-LRP \u03c0\u03b1\u03c1\u03ac\u03b3\u03b5\u03b9 \u03b5\u03be\u03b7\u03b3\u03ae\u03c3\u03b5\u03b9\u03c2 \u03c3\u03c4\u03b1 \u03c0\u03b5\u03b4\u03af\u03b1 \u03c4\u03bf\u03c5 \u03c7\u03c1\u03cc\u03bd\u03bf\u03c5, \u03c4\u03b7\u03c2 \u03c3\u03c5\u03c7\u03bd\u03cc\u03c4\u03b7\u03c4\u03b1\u03c2 \u03ba\u03b1\u03b9 \u03c7\u03c1\u03cc\u03bd\u03bf\u03c5-\u03c3\u03c5\u03c7\u03bd\u03cc\u03c4\u03b7\u03c4\u03b1\u03c2 \u03b3\u03b9\u03b1 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03b1 \u03bc\u03b5 time-domain input. \u03a3\u03c5\u03bd\u03b4\u03c5\u03ac\u03b6\u03b5\u03b9 Fourier transforms \u03bc\u03b5 Layer-wise Relevance Propagation \u03ba\u03b1\u03b9 \u03ad\u03c7\u03b5\u03b9 \u03b1\u03bd\u03b1\u03c0\u03c4\u03c5\u03c7\u03b8\u03b5\u03af \u03b3\u03b9\u03b1 \u03bc\u03bf\u03bd\u03bf\u03bc\u03b5\u03c4\u03b1\u03b2\u03bb\u03b7\u03c4\u03ac \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03b1. \u03a3\u03c4\u03bf \u03bf\u03b9\u03ba\u03bf\u03c3\u03cd\u03c3\u03c4\u03b7\u03bc\u03b1 \u03c4\u03b7\u03c2 \u03bc\u03b5\u03bb\u03ad\u03c4\u03b7\u03c2 \u03c5\u03bb\u03bf\u03c0\u03bf\u03b9\u03b5\u03af\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc \u03c4\u03bf SIGN-XAI-2.<\/p>\n<p>\u0397 \u03c3\u03c0\u03b1\u03bd\u03b9\u03cc\u03c4\u03b7\u03c4\u03b1 \u03ad\u03c7\u03b5\u03b9 \u03c0\u03c1\u03b1\u03ba\u03c4\u03b9\u03ba\u03cc \u03b2\u03ac\u03c1\u03bf\u03c2. \u03a3\u03b5 \u03ae\u03c7\u03bf, \u03b2\u03b9\u03bf\u03ca\u03b1\u03c4\u03c1\u03b9\u03ba\u03ac \u03c3\u03ae\u03bc\u03b1\u03c4\u03b1 \u03ba\u03b1\u03b9 \u03b5\u03c6\u03b1\u03c1\u03bc\u03bf\u03b3\u03ad\u03c2 \u03b1\u03b9\u03c3\u03b8\u03b7\u03c4\u03ae\u03c1\u03c9\u03bd, \u03ad\u03bd\u03b1 \u03bc\u03bf\u03c4\u03af\u03b2\u03bf \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03bc\u03b7 \u03c6\u03b1\u03af\u03bd\u03b5\u03c4\u03b1\u03b9 \u03ba\u03b1\u03b8\u03b1\u03c1\u03ac \u03c3\u03c4\u03bf \u03c7\u03c1\u03bf\u03bd\u03b9\u03ba\u03cc \u03b4\u03b9\u03ac\u03b3\u03c1\u03b1\u03bc\u03bc\u03b1 \u03b1\u03bb\u03bb\u03ac \u03bd\u03b1 \u03b3\u03af\u03bd\u03b5\u03c4\u03b1\u03b9 \u03b5\u03bc\u03c6\u03b1\u03bd\u03ad\u03c2 \u03c3\u03c4\u03b7 \u03c3\u03c5\u03c7\u03bd\u03cc\u03c4\u03b7\u03c4\u03b1. \u0397 \u03b5\u03c1\u03b3\u03b1\u03c3\u03af\u03b1 \u03c0\u03b1\u03c1\u03bf\u03c5\u03c3\u03b9\u03ac\u03b6\u03b5\u03b9 \u03c0\u03b1\u03c1\u03ac\u03b4\u03b5\u03b9\u03b3\u03bc\u03b1 \u03b1\u03c0\u03cc AudioMNIST, \u03cc\u03c0\u03bf\u03c5 \u03b7 \u03b4\u03b9\u03ac\u03ba\u03c1\u03b9\u03c3\u03b7 \u03c6\u03cd\u03bb\u03bf\u03c5 \u03bf\u03bc\u03b9\u03bb\u03b7\u03c4\u03ae \u03b3\u03b9\u03b1 \u03c4\u03bf \u03af\u03b4\u03b9\u03bf \u03c8\u03b7\u03c6\u03af\u03bf \u03b5\u03af\u03bd\u03b1\u03b9 \u03c3\u03b1\u03c6\u03ad\u03c3\u03c4\u03b5\u03c1\u03b7 \u03c3\u03c4\u03bf frequency domain. \u03a3\u03c4\u03bf \u03c0\u03b5\u03af\u03c1\u03b1\u03bc\u03b1 \u03bc\u03b5 1.200 \u03b5\u03b3\u03b3\u03c1\u03b1\u03c6\u03ad\u03c2 \u03ba\u03b1\u03b9 100% test accuracy, \u03bf\u03b9 \u03c5\u03c8\u03b7\u03bb\u03cc\u03c4\u03b5\u03c1\u03b5\u03c2 relevance \u03c4\u03b9\u03bc\u03ad\u03c2 \u03c4\u03b7\u03c2 DFT-LRP \u03c3\u03c5\u03b3\u03ba\u03b5\u03bd\u03c4\u03c1\u03ce\u03b8\u03b7\u03ba\u03b1\u03bd \u03c3\u03c4\u03b9\u03c2 \u03b1\u03bd\u03b1\u03bc\u03b5\u03bd\u03cc\u03bc\u03b5\u03bd\u03b5\u03c2 \u03c0\u03b5\u03c1\u03b9\u03bf\u03c7\u03ad\u03c2 \u03c3\u03c5\u03c7\u03bd\u03bf\u03c4\u03ae\u03c4\u03c9\u03bd \u03c4\u03c9\u03bd \u03b4\u03cd\u03bf \u03b4\u03b5\u03b9\u03b3\u03bc\u03ac\u03c4\u03c9\u03bd.<\/p>\n<p>\u0394\u03b5\u03bd \u03c0\u03c1\u03bf\u03ba\u03cd\u03c0\u03c4\u03b5\u03b9 \u03cc\u03c4\u03b9 \u03ba\u03ac\u03b8\u03b5 \u03b5\u03c6\u03b1\u03c1\u03bc\u03bf\u03b3\u03ae \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 Fourier-based explanation. \u03a0\u03c1\u03bf\u03ba\u03cd\u03c0\u03c4\u03b5\u03b9 \u03cc\u03c4\u03b9 \u03b7 \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ae domain \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b1\u03b9\u03c4\u03b9\u03bf\u03bb\u03bf\u03b3\u03b5\u03af\u03c4\u03b1\u03b9. \u0391\u03bd \u03b7 \u03b1\u03c0\u03cc\u03c6\u03b1\u03c3\u03b7 \u03b1\u03c6\u03bf\u03c1\u03ac \u03b4\u03cc\u03bd\u03b7\u03c3\u03b7 \u03bc\u03b7\u03c7\u03b1\u03bd\u03ae\u03c2, \u03c6\u03c9\u03bd\u03b7\u03c4\u03b9\u03ba\u03cc \u03c3\u03ae\u03bc\u03b1 \u03ae ECG, \u03bc\u03b9\u03b1 \u03b1\u03c0\u03bf\u03ba\u03bb\u03b5\u03b9\u03c3\u03c4\u03b9\u03ba\u03ac time-domain \u03b5\u03be\u03ae\u03b3\u03b7\u03c3\u03b7 \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03ad\u03bb\u03b5\u03b3\u03c7\u03bf \u03cc\u03c4\u03b9 \u03b4\u03b5\u03bd \u03b1\u03c0\u03bf\u03ba\u03c1\u03cd\u03c0\u03c4\u03b5\u03b9 \u03c3\u03b7\u03bc\u03b1\u03bd\u03c4\u03b9\u03ba\u03ae \u03c0\u03bb\u03b7\u03c1\u03bf\u03c6\u03bf\u03c1\u03af\u03b1.<\/p>\n<h2 id=\"cross-channel-dependencies\">\u039f\u03b9 \u03c3\u03c7\u03ad\u03c3\u03b5\u03b9\u03c2 \u03b1\u03bd\u03ac\u03bc\u03b5\u03c3\u03b1 \u03c3\u03c4\u03b1 \u03ba\u03b1\u03bd\u03ac\u03bb\u03b9\u03b1<\/h2>\n<p>\u039f\u03b9 \u03c0\u03b5\u03c1\u03b9\u03c3\u03c3\u03cc\u03c4\u03b5\u03c1\u03b5\u03c2 \u03bc\u03ad\u03b8\u03bf\u03b4\u03bf\u03b9 \u03bc\u03c0\u03bf\u03c1\u03bf\u03cd\u03bd \u03bd\u03b1 \u03b5\u03c0\u03b9\u03c3\u03b7\u03bc\u03ac\u03bd\u03bf\u03c5\u03bd \u03c3\u03b7\u03bc\u03b1\u03bd\u03c4\u03b9\u03ba\u03ad\u03c2 \u03c0\u03b5\u03c1\u03b9\u03bf\u03c7\u03ad\u03c2 \u03c3\u03b5 \u03c0\u03bf\u03bb\u03bb\u03ac \u03ba\u03b1\u03bd\u03ac\u03bb\u03b9\u03b1, \u03b1\u03bb\u03bb\u03ac \u03b1\u03c5\u03c4\u03cc \u03b4\u03b5\u03bd \u03c3\u03b7\u03bc\u03b1\u03af\u03bd\u03b5\u03b9 \u03cc\u03c4\u03b9 \u03b5\u03be\u03b7\u03b3\u03bf\u03cd\u03bd \u03c4\u03b9\u03c2 \u03b5\u03be\u03b1\u03c1\u03c4\u03ae\u03c3\u03b5\u03b9\u03c2 \u03bc\u03b5\u03c4\u03b1\u03be\u03cd \u03c4\u03bf\u03c5\u03c2. \u03a3\u03b5 \u03ad\u03bd\u03b1 multivariate \u03c3\u03ae\u03bc\u03b1, \u03b4\u03cd\u03bf \u03ba\u03b1\u03bd\u03ac\u03bb\u03b9\u03b1 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b1\u03c0\u03bf\u03ba\u03c4\u03bf\u03cd\u03bd \u03c3\u03b7\u03bc\u03b1\u03c3\u03af\u03b1 \u03b5\u03c0\u03b5\u03b9\u03b4\u03ae \u03bc\u03b5\u03c4\u03b1\u03b2\u03ac\u03bb\u03bb\u03bf\u03bd\u03c4\u03b1\u03b9 \u03bc\u03b1\u03b6\u03af \u03c4\u03b7\u03bd \u03af\u03b4\u03b9\u03b1 \u03c3\u03c4\u03b9\u03b3\u03bc\u03ae \u03ae \u03b5\u03c0\u03b5\u03b9\u03b4\u03ae \u03c4\u03bf \u03ad\u03bd\u03b1 \u03c0\u03c1\u03bf\u03b7\u03b3\u03b5\u03af\u03c4\u03b1\u03b9 \u03c4\u03bf\u03c5 \u03ac\u03bb\u03bb\u03bf\u03c5.<\/p>\n<p>\u0397 \u03b1\u03bd\u03b1\u03c3\u03ba\u03cc\u03c0\u03b7\u03c3\u03b7 \u03b5\u03c0\u03b9\u03c3\u03b7\u03bc\u03b1\u03af\u03bd\u03b5\u03b9 \u03cc\u03c4\u03b9 \u03c4\u03b1 \u03c3\u03c5\u03bd\u03b7\u03b8\u03b9\u03c3\u03bc\u03ad\u03bd\u03b1 relevance heatmaps \u03b4\u03b5\u03bd \u03b4\u03b9\u03b1\u03b8\u03ad\u03c4\u03bf\u03c5\u03bd \u03c4\u03b7\u03bd \u03c0\u03c1\u03cc\u03c3\u03b8\u03b5\u03c4\u03b7 \u03b4\u03b9\u03ac\u03c3\u03c4\u03b1\u03c3\u03b7 \u03c0\u03bf\u03c5 \u03b1\u03c0\u03b1\u03b9\u03c4\u03b5\u03af\u03c4\u03b1\u03b9 \u03b3\u03b9\u03b1 \u03bd\u03b1 \u03b1\u03bd\u03b1\u03c0\u03b1\u03c1\u03b1\u03c3\u03c4\u03ae\u03c3\u03bf\u03c5\u03bd \u03c3\u03cd\u03b3\u03c7\u03c1\u03bf\u03bd\u03b5\u03c2 \u03ba\u03b1\u03b9 \u03b1\u03c3\u03cd\u03b3\u03c7\u03c1\u03bf\u03bd\u03b5\u03c2 cross-channel dependencies. \u0397 \u03bc\u03ad\u03b8\u03bf\u03b4\u03bf\u03c2 PAX-TS \u03b1\u03bd\u03c4\u03b9\u03bc\u03b5\u03c4\u03c9\u03c0\u03af\u03b6\u03b5\u03b9 \u03c4\u03ad\u03c4\u03bf\u03b9\u03b5\u03c2 \u03c3\u03c7\u03ad\u03c3\u03b5\u03b9\u03c2 \u03c3\u03b5 forecasting \u03bc\u03ad\u03c3\u03c9 localized perturbations, \u03b1\u03bb\u03bb\u03ac \u03bc\u03b5 \u03bc\u03b5\u03b3\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03bf \u03c5\u03c0\u03bf\u03bb\u03bf\u03b3\u03b9\u03c3\u03c4\u03b9\u03ba\u03cc \u03ba\u03cc\u03c3\u03c4\u03bf\u03c2. \u039f\u03b9 \u03c3\u03c5\u03b3\u03b3\u03c1\u03b1\u03c6\u03b5\u03af\u03c2 \u03c0\u03b1\u03c1\u03bf\u03c5\u03c3\u03b9\u03ac\u03b6\u03bf\u03c5\u03bd \u03c4\u03b7\u03bd \u03ba\u03b1\u03c4\u03b5\u03cd\u03b8\u03c5\u03bd\u03c3\u03b7 \u03c9\u03c2 trade-off \u03ba\u03b1\u03b9 \u03cc\u03c7\u03b9 \u03c9\u03c2 \u03ba\u03b1\u03b8\u03bf\u03bb\u03b9\u03ba\u03ae \u03bb\u03cd\u03c3\u03b7.<\/p>\n<p>\u03a3\u03b5 \u03ad\u03bd\u03b1 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03cc project, \u03b7 \u03bf\u03bc\u03ac\u03b4\u03b1 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03bf\u03c1\u03af\u03c3\u03b5\u03b9 \u03c0\u03c1\u03ce\u03c4\u03b1 \u03c0\u03bf\u03b9\u03b1 \u03c3\u03c7\u03ad\u03c3\u03b7 \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03bd\u03b1 \u03ba\u03b1\u03c4\u03b1\u03bd\u03bf\u03ae\u03c3\u03b5\u03b9 \u03bf \u03c7\u03c1\u03ae\u03c3\u03c4\u03b7\u03c2, \u03c0\u03cc\u03c3\u03bf \u03b3\u03c1\u03ae\u03b3\u03bf\u03c1\u03b1 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03c0\u03b1\u03c1\u03b1\u03c7\u03b8\u03b5\u03af \u03b7 \u03b5\u03be\u03ae\u03b3\u03b7\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03b1\u03bd \u03c4\u03bf \u03b5\u03c0\u03b9\u03c0\u03bb\u03ad\u03bf\u03bd compute \u03b4\u03b9\u03ba\u03b1\u03b9\u03bf\u03bb\u03bf\u03b3\u03b5\u03af\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc \u03c4\u03bf \u03c1\u03af\u03c3\u03ba\u03bf. \u0397 \u03b1\u03bd\u03ac\u03b3\u03ba\u03b7 \u03b1\u03c5\u03c4\u03ae \u03b8\u03c5\u03bc\u03af\u03b6\u03b5\u03b9 \u03c4\u03bf <a href=\"https:\/\/twodots.gr\/geographic-domain-shift-ai-modelo-se-nees-agores\/\">geographic domain shift<\/a>: \u03bc\u03b9\u03b1 \u03b5\u03be\u03ae\u03b3\u03b7\u03c3\u03b7 \u03c0\u03bf\u03c5 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b5\u03c0\u03b1\u03c1\u03ba\u03ae\u03c2 \u03c3\u03b5 \u03ad\u03bd\u03b1 dataset \u03ae \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03b9\u03ba\u03cc \u03c0\u03b5\u03c1\u03b9\u03b2\u03ac\u03bb\u03bb\u03bf\u03bd \u03b4\u03b5\u03bd \u03b8\u03b5\u03c9\u03c1\u03b5\u03af\u03c4\u03b1\u03b9 \u03b1\u03c5\u03c4\u03cc\u03bc\u03b1\u03c4\u03b1 \u03b5\u03c0\u03b1\u03c1\u03ba\u03ae\u03c2 \u03c3\u03b5 \u03ac\u03bb\u03bb\u03bf.<\/p>\n<h2 id=\"metrics-time-series\">52 metrics, \u03b1\u03bb\u03bb\u03ac \u03bc\u03cc\u03bd\u03bf \u03b4\u03cd\u03bf \u03b5\u03b9\u03b4\u03b9\u03ba\u03ac \u03b3\u03b9\u03b1 time series<\/h2>\n<p>\u0397 \u03b1\u03bd\u03b1\u03c3\u03ba\u03cc\u03c0\u03b7\u03c3\u03b7 \u03b5\u03bd\u03c4\u03cc\u03c0\u03b9\u03c3\u03b5 52 metrics: 27 perturbation-based, 15 ground-truth-based \u03ba\u03b1\u03b9 \u03b4\u03ad\u03ba\u03b1 \u03ac\u03bb\u03bb\u03bf\u03c5 \u03c4\u03cd\u03c0\u03bf\u03c5. \u0391\u03c0\u03cc \u03b1\u03c5\u03c4\u03ac, 44 \u03b8\u03b5\u03c9\u03c1\u03bf\u03cd\u03bd\u03c4\u03b1\u03b9 \u03c3\u03c5\u03bc\u03b2\u03b1\u03c4\u03ac \u03bc\u03b5 \u03c7\u03c1\u03bf\u03bd\u03bf\u03c3\u03b5\u03b9\u03c1\u03ad\u03c2, \u03ad\u03be\u03b9 \u03c0\u03b5\u03c1\u03b9\u03bf\u03c1\u03af\u03b6\u03bf\u03bd\u03c4\u03b1\u03b9 \u03c3\u03b5 \u03b5\u03b9\u03ba\u03cc\u03bd\u03b5\u03c2 \u03ba\u03b1\u03b9 \u03bc\u03cc\u03bd\u03bf \u03b4\u03cd\u03bf \u03c3\u03c7\u03b5\u03b4\u03b9\u03ac\u03c3\u03c4\u03b7\u03ba\u03b1\u03bd \u03b5\u03b9\u03b4\u03b9\u03ba\u03ac \u03b3\u03b9\u03b1 time series: Mask Information \u03ba\u03b1\u03b9 Mask Entropy. \u039a\u03b1\u03b9 \u03c4\u03b1 \u03b4\u03cd\u03bf \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03bf\u03cd\u03bd \u03c3\u03b5 \u03c5\u03c0\u03bf\u03b1\u03ba\u03bf\u03bb\u03bf\u03c5\u03b8\u03af\u03b5\u03c2 \u03ba\u03b1\u03b9 \u03bc\u03b5\u03c4\u03c1\u03bf\u03cd\u03bd \u03c0\u03cc\u03c3\u03bf \u03ba\u03b1\u03bb\u03ac \u03c4\u03bf \u03c0\u03c1\u03bf\u03b2\u03bb\u03b5\u03c0\u03cc\u03bc\u03b5\u03bd\u03bf relevance \u03c4\u03b1\u03b9\u03c1\u03b9\u03ac\u03b6\u03b5\u03b9 \u03c3\u03b5 ground-truth mask.<\/p>\n<p>\u039a\u03b1\u03bd\u03ad\u03bd\u03b1 \u03b1\u03c0\u03cc \u03c4\u03b1 metrics \u03c4\u03b7\u03c2 \u03b1\u03bd\u03b1\u03c3\u03ba\u03cc\u03c0\u03b7\u03c3\u03b7\u03c2 \u03b4\u03b5\u03bd \u03ad\u03c7\u03b5\u03b9 \u03b1\u03bd\u03b1\u03c0\u03c4\u03c5\u03c7\u03b8\u03b5\u03af \u03b5\u03b9\u03b4\u03b9\u03ba\u03ac \u03b3\u03b9\u03b1 \u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7 explanations \u03c3\u03c4\u03b7 \u03c3\u03c5\u03c7\u03bd\u03cc\u03c4\u03b7\u03c4\u03b1 \u03ae \u03c3\u03c4\u03bf time-frequency domain. \u0397 \u03bc\u03b5\u03c4\u03b1\u03c6\u03bf\u03c1\u03ac \u03b5\u03bd\u03cc\u03c2 perturbation metric \u03b5\u03ba\u03b5\u03af \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03b1\u03c0\u03bb\u03ae: \u03bc\u03b9\u03b1 \u03bc\u03b9\u03ba\u03c1\u03ae \u03b1\u03bb\u03bb\u03b1\u03b3\u03ae \u03c3\u03c4\u03b7 \u03c3\u03c5\u03c7\u03bd\u03cc\u03c4\u03b7\u03c4\u03b1 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b5\u03c0\u03b7\u03c1\u03b5\u03ac\u03c3\u03b5\u03b9 \u03bf\u03bb\u03cc\u03ba\u03bb\u03b7\u03c1\u03bf \u03c4\u03bf \u03c3\u03ae\u03bc\u03b1 \u03c3\u03c4\u03bf\u03bd \u03c7\u03c1\u03cc\u03bd\u03bf. \u0391\u03c1\u03ba\u03b5\u03c4\u03ac metrics \u03c5\u03c0\u03bf\u03b8\u03ad\u03c4\u03bf\u03c5\u03bd \u03b5\u03c0\u03af\u03c3\u03b7\u03c2 \u03b1\u03bd\u03b5\u03be\u03b1\u03c1\u03c4\u03b7\u03c3\u03af\u03b1 \u03bc\u03b5\u03c4\u03b1\u03be\u03cd features, \u03c5\u03c0\u03cc\u03b8\u03b5\u03c3\u03b7 \u03c0\u03bf\u03c5 \u03c3\u03c5\u03b3\u03ba\u03c1\u03bf\u03cd\u03b5\u03c4\u03b1\u03b9 \u03bc\u03b5 temporal \u03ba\u03b1\u03b9 cross-channel dependencies.<\/p>\n<p>\u0393\u03b9\u03b1 \u03bc\u03b9\u03b1 \u03bf\u03bc\u03ac\u03b4\u03b1 governance, \u03c4\u03bf \u03bc\u03ac\u03b8\u03b7\u03bc\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c3\u03b1\u03c6\u03ad\u03c2. \u0394\u03b5\u03bd \u03b1\u03c1\u03ba\u03b5\u03af \u03bd\u03b1 \u03b5\u03c0\u03b9\u03bb\u03ad\u03be\u03b5\u03b9 metric \u03b5\u03c0\u03b5\u03b9\u03b4\u03ae \u03c0\u03b5\u03c1\u03b9\u03bb\u03b1\u03bc\u03b2\u03ac\u03bd\u03b5\u03c4\u03b1\u03b9 \u03c3\u03b5 \u03b4\u03b7\u03bc\u03bf\u03c6\u03b9\u03bb\u03ae \u03b2\u03b9\u03b2\u03bb\u03b9\u03bf\u03b8\u03ae\u03ba\u03b7. \u03a7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03bd\u03b1 \u03c4\u03b5\u03ba\u03bc\u03b7\u03c1\u03b9\u03ce\u03c3\u03b5\u03b9 \u03c0\u03bf\u03b9\u03b1 \u03b9\u03b4\u03b9\u03cc\u03c4\u03b7\u03c4\u03b1 \u03bc\u03b5\u03c4\u03c1\u03ac, \u03c0\u03bf\u03b9\u03b5\u03c2 \u03c5\u03c0\u03bf\u03b8\u03ad\u03c3\u03b5\u03b9\u03c2 \u03ba\u03ac\u03bd\u03b5\u03b9 \u03ba\u03b1\u03b9 \u03b1\u03bd \u03b1\u03c5\u03c4\u03ad\u03c2 \u03b9\u03c3\u03c7\u03cd\u03bf\u03c5\u03bd \u03b3\u03b9\u03b1 \u03c4\u03bf \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03bf \u03c3\u03ae\u03bc\u03b1. \u038c\u03c0\u03c9\u03c2 \u03b4\u03b5\u03af\u03c7\u03bd\u03bf\u03c5\u03bd \u03ba\u03b1\u03b9 \u03c4\u03b1 <a href=\"https:\/\/twodots.gr\/klinika-oria-ai-provlepseis-katanohites\/\">\u03ba\u03bb\u03b9\u03bd\u03b9\u03ba\u03ac \u03cc\u03c1\u03b9\u03b1 \u03c3\u03c4\u03b7\u03bd AI<\/a>, \u03c4\u03bf \u03c0\u03b9\u03bf \u03ba\u03b1\u03c4\u03b1\u03bd\u03bf\u03b7\u03c4\u03cc \u03b1\u03c0\u03bf\u03c4\u03ad\u03bb\u03b5\u03c3\u03bc\u03b1 \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03b1\u03bd\u03b1\u03b3\u03ba\u03b1\u03c3\u03c4\u03b9\u03ba\u03ac \u03ba\u03b1\u03b9 \u03c4\u03bf \u03c0\u03b9\u03bf \u03c0\u03b9\u03c3\u03c4\u03cc.<\/p>\n<h2 id=\"benchmarks-ground-truth\">Benchmarks \u03ba\u03b1\u03b9 \u03c4\u03bf \u03c0\u03c1\u03cc\u03b2\u03bb\u03b7\u03bc\u03b1 \u03c4\u03bf\u03c5 ground truth<\/h2>\n<p>\u039c\u03cc\u03bd\u03bf \u03c4\u03c1\u03af\u03b1 \u03b1\u03c0\u03cc \u03c4\u03b1 \u03ad\u03be\u03b9 frameworks \u03c0\u03c1\u03bf\u03c3\u03c6\u03ad\u03c1\u03bf\u03c5\u03bd datasets \u03b3\u03b9\u03b1 \u03c3\u03c5\u03b3\u03ba\u03c1\u03b9\u03c4\u03b9\u03ba\u03ae \u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7: XTSC-Bench, TSInterpret \u03ba\u03b1\u03b9 time_interpret. \u03a4\u03bf XTSC-Bench \u03c0\u03b5\u03c1\u03b9\u03bb\u03b1\u03bc\u03b2\u03ac\u03bd\u03b5\u03b9 \u03ad\u03be\u03b9 synthetic datasets \u03bc\u03b5 ground-truth \u03c0\u03bb\u03b7\u03c1\u03bf\u03c6\u03bf\u03c1\u03af\u03b1, \u03ba\u03b1\u03b8\u03ce\u03c2 \u03ba\u03b1\u03b9 \u03c0\u03c1\u03cc\u03c3\u03b2\u03b1\u03c3\u03b7 \u03c3\u03c4\u03b1 UCR \u03ba\u03b1\u03b9 UEA archives, \u03c4\u03b1 \u03bf\u03c0\u03bf\u03af\u03b1 \u03c3\u03c4\u03b7\u03bd \u03b5\u03c1\u03b3\u03b1\u03c3\u03af\u03b1 \u03b1\u03c1\u03b9\u03b8\u03bc\u03bf\u03cd\u03bd 128 \u03ba\u03b1\u03b9 30 datasets \u03b1\u03bd\u03c4\u03af\u03c3\u03c4\u03bf\u03b9\u03c7\u03b1. \u03a4\u03bf time_interpret \u03c0\u03b1\u03c1\u03ad\u03c7\u03b5\u03b9 \u03c0\u03ad\u03bd\u03c4\u03b5 datasets, \u03b1\u03c0\u03cc \u03c4\u03b1 \u03bf\u03c0\u03bf\u03af\u03b1 \u03c4\u03c1\u03af\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c3\u03c5\u03bd\u03b8\u03b5\u03c4\u03b9\u03ba\u03ac \u03ba\u03b1\u03b9 \u03b4\u03cd\u03bf \u03ba\u03bb\u03b9\u03bd\u03b9\u03ba\u03ac.<\/p>\n<p>\u038c\u03bb\u03b1 \u03c4\u03b1 datasets \u03bc\u03b5 \u03b4\u03b9\u03b1\u03b8\u03ad\u03c3\u03b9\u03bc\u03bf ground truth \u03b2\u03b1\u03c3\u03af\u03b6\u03bf\u03bd\u03c4\u03b1\u03b9 \u03c3\u03b5 \u03c3\u03c5\u03bd\u03b8\u03b5\u03c4\u03b9\u03ba\u03ac \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03b1 \u03ae \u03c0\u03c1\u03bf\u03ba\u03b1\u03b8\u03bf\u03c1\u03b9\u03c3\u03bc\u03ad\u03bd\u03b5\u03c2 \u03ba\u03b1\u03c4\u03b1\u03bd\u03bf\u03bc\u03ad\u03c2. \u0391\u03c5\u03c4\u03cc \u03b2\u03bf\u03b7\u03b8\u03ac \u03c3\u03c4\u03bf\u03bd \u03b5\u03bb\u03b5\u03b3\u03c7\u03cc\u03bc\u03b5\u03bd\u03bf \u03ad\u03bb\u03b5\u03b3\u03c7\u03bf, \u03b1\u03bb\u03bb\u03ac \u03b4\u03b5\u03bd \u03b1\u03c0\u03bf\u03b4\u03b5\u03b9\u03ba\u03bd\u03cd\u03b5\u03b9 \u03cc\u03c4\u03b9 \u03b7 \u03bc\u03ad\u03b8\u03bf\u03b4\u03bf\u03c2 \u03b8\u03b1 \u03b5\u03be\u03b7\u03b3\u03ae\u03c3\u03b5\u03b9 \u03c3\u03c9\u03c3\u03c4\u03ac \u03ad\u03bd\u03b1 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03cc ECG, \u03bc\u03b9\u03b1 \u03b3\u03c1\u03b1\u03bc\u03bc\u03ae \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae\u03c2 \u03ae \u03ad\u03bd\u03b1 \u03c3\u03cd\u03bd\u03b8\u03b5\u03c4\u03bf customer-behavior signal. \u03a4\u03b1 \u03ba\u03bb\u03b9\u03bd\u03b9\u03ba\u03ac datasets \u03c4\u03b7\u03c2 \u03b1\u03bd\u03b1\u03c3\u03ba\u03cc\u03c0\u03b7\u03c3\u03b7\u03c2 \u03b4\u03b5\u03bd \u03b4\u03b9\u03b1\u03b8\u03ad\u03c4\u03bf\u03c5\u03bd ground-truth explanations.<\/p>\n<p>\u0397 \u03c3\u03c9\u03c3\u03c4\u03ae \u03c7\u03c1\u03ae\u03c3\u03b7 benchmark \u03b5\u03af\u03bd\u03b1\u03b9 \u03c9\u03c2 \u03ad\u03bd\u03b1 \u03b5\u03c0\u03af\u03c0\u03b5\u03b4\u03bf \u03c4\u03b5\u03ba\u03bc\u03b7\u03c1\u03af\u03c9\u03c3\u03b7\u03c2, \u03cc\u03c7\u03b9 \u03c9\u03c2 \u03c4\u03b5\u03bb\u03b9\u03ba\u03ae \u03c0\u03b9\u03c3\u03c4\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7. \u039c\u03b9\u03b1 \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03b9\u03ba\u03ae \u03b5\u03c6\u03b1\u03c1\u03bc\u03bf\u03b3\u03ae \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 domain-expert review, \u03b5\u03bb\u03ad\u03b3\u03c7\u03bf\u03c5\u03c2 \u03c3\u03c4\u03b1 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ac data distributions \u03ba\u03b1\u03b9 monitoring \u03bc\u03b5\u03c4\u03ac \u03c4\u03bf deployment. \u0397 \u03bf\u03bc\u03ac\u03b4\u03b1 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03b5\u03b9 \u03ba\u03b1\u03b9 <a href=\"https:\/\/twodots.gr\/ergaleia-statistikis-analysis-epicheiriseis-2026\/\">\u03b5\u03c1\u03b3\u03b1\u03bb\u03b5\u03af\u03b1 \u03c3\u03c4\u03b1\u03c4\u03b9\u03c3\u03c4\u03b9\u03ba\u03ae\u03c2 \u03b1\u03bd\u03ac\u03bb\u03c5\u03c3\u03b7\u03c2<\/a> \u03b3\u03b9\u03b1 stability, drift \u03ba\u03b1\u03b9 confidence intervals, \u03b1\u03bb\u03bb\u03ac \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03ba\u03c1\u03b1\u03c4\u03ae\u03c3\u03b5\u03b9 \u03b4\u03b9\u03b1\u03ba\u03c1\u03b9\u03c4\u03cc \u03c4\u03bf prediction quality \u03b1\u03c0\u03cc \u03c4\u03bf explanation quality.<\/p>\n<h2 id=\"framework-allazei-exigisi\">\u038c\u03c4\u03b1\u03bd \u03c4\u03bf framework \u03b1\u03bb\u03bb\u03ac\u03b6\u03b5\u03b9 \u03c4\u03b7\u03bd \u03b5\u03be\u03ae\u03b3\u03b7\u03c3\u03b7<\/h2>\n<p>\u03a4\u03bf \u03c0\u03b9\u03bf \u03c7\u03b5\u03b9\u03c1\u03bf\u03c0\u03b9\u03b1\u03c3\u03c4\u03cc \u03b5\u03cd\u03c1\u03b7\u03bc\u03b1 \u03b1\u03c6\u03bf\u03c1\u03ac \u03c4\u03b7\u03bd \u03b1\u03bd\u03b1\u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03b9\u03bc\u03cc\u03c4\u03b7\u03c4\u03b1. \u039f\u03b9 \u03b5\u03c1\u03b5\u03c5\u03bd\u03b7\u03c4\u03ad\u03c2 \u03b5\u03ba\u03c0\u03b1\u03af\u03b4\u03b5\u03c5\u03c3\u03b1\u03bd convolutional neural network \u03b3\u03b9\u03b1 20 epochs \u03c3\u03b5 ECG records \u03bc\u03b5 right bundle branch block \u03ba\u03b1\u03b9 \u03b9\u03c3\u03ac\u03c1\u03b9\u03b8\u03bc\u03b1 \u03c5\u03b3\u03b9\u03ae \u03b4\u03b5\u03af\u03b3\u03bc\u03b1\u03c4\u03b1 \u03b1\u03c0\u03cc \u03c4\u03bf PTB-XL. \u03a7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b1\u03bd 3.316 \u03b5\u03b3\u03b3\u03c1\u03b1\u03c6\u03ad\u03c2, split 80\/10\/10 \u03ba\u03b1\u03b9 \u03b1\u03bd\u03ad\u03c6\u03b5\u03c1\u03b1\u03bd test accuracy 96,98%.<\/p>\n<p>\u0393\u03b9\u03b1 \u03c4\u03b9\u03c2 \u03b5\u03be\u03b7\u03b3\u03ae\u03c3\u03b5\u03b9\u03c2 \u03c3\u03c5\u03bd\u03ad\u03ba\u03c1\u03b9\u03bd\u03b1\u03bd \u03c4\u03bf Integrated Gradients \u03cc\u03c0\u03c9\u03c2 \u03c5\u03bb\u03bf\u03c0\u03bf\u03b9\u03b5\u03af\u03c4\u03b1\u03b9 \u03c3\u03c4\u03bf TSInterpret \u03bc\u03ad\u03c3\u03c9 Captum \u03ba\u03b1\u03b9 \u03c3\u03c4\u03bf SIGN-XAI-2 \u03bc\u03ad\u03c3\u03c9 Zennit. \u039f\u03b9 \u03b5\u03bc\u03c6\u03b1\u03bd\u03b5\u03af\u03c2 \u03c0\u03b1\u03c1\u03ac\u03bc\u03b5\u03c4\u03c1\u03bf\u03b9 \u03ae\u03c4\u03b1\u03bd \u03af\u03b4\u03b9\u03b5\u03c2: zero baseline \u03ba\u03b1\u03b9 50 interpolation steps. \u03a0\u03b1\u03c1\u2019 \u03cc\u03bb\u03b1 \u03b1\u03c5\u03c4\u03ac, \u03bf\u03b9 relevance distributions \u03b4\u03b9\u03ad\u03c6\u03b5\u03c1\u03b1\u03bd \u03b1\u03b9\u03c3\u03b8\u03b7\u03c4\u03ac. \u0397 Zennit-based \u03c5\u03bb\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7 \u03b1\u03bd\u03ad\u03b4\u03b5\u03b9\u03be\u03b5 \u03c4\u03bf \u03b1\u03bd\u03b1\u03bc\u03b5\u03bd\u03cc\u03bc\u03b5\u03bd\u03bf \u03c3\u03c7\u03ae\u03bc\u03b1 \u03c4\u03bf\u03c5 RBBB \u03c3\u03c4\u03bf \u03b5\u03be\u03b5\u03c4\u03b1\u03b6\u03cc\u03bc\u03b5\u03bd\u03bf lead, \u03b5\u03bd\u03ce \u03b7 Captum-based \u03b5\u03be\u03ae\u03b3\u03b7\u03c3\u03b7 \u03b4\u03b5\u03bd \u03c4\u03bf \u03b5\u03bc\u03c6\u03ac\u03bd\u03b9\u03c3\u03b5 \u03bc\u03b5 \u03c4\u03bf\u03bd \u03af\u03b4\u03b9\u03bf \u03c4\u03c1\u03cc\u03c0\u03bf.<\/p>\n<p>\u03a3\u03c4\u03bf test set \u03c4\u03c9\u03bd 443 \u03c0\u03b5\u03c1\u03b9\u03c0\u03c4\u03ce\u03c3\u03b5\u03c9\u03bd, \u03b7 \u03bc\u03ad\u03c3\u03b7 Spearman rank correlation \u03ae\u03c4\u03b1\u03bd -0,14, \u03b7 \u03b4\u03b9\u03ac\u03bc\u03b5\u03c3\u03bf\u03c2 -0,17 \u03ba\u03b1\u03b9 \u03b7 \u03c4\u03c5\u03c0\u03b9\u03ba\u03ae \u03b1\u03c0\u03cc\u03ba\u03bb\u03b9\u03c3\u03b7 0,11. \u039a\u03b1\u03bc\u03af\u03b1 \u03c0\u03b5\u03c1\u03af\u03c0\u03c4\u03c9\u03c3\u03b7 \u03b4\u03b5\u03bd \u03b5\u03af\u03c7\u03b5 rho \u03c0\u03ac\u03bd\u03c9 \u03b1\u03c0\u03cc 0,5. \u03a4\u03bf Jaccard overlap \u03c3\u03c4\u03bf \u03ba\u03bf\u03c1\u03c5\u03c6\u03b1\u03af\u03bf 5% \u03c4\u03c9\u03bd relevance points \u03ae\u03c4\u03b1\u03bd 0,26 \u00b1 0,09. \u039f\u03b9 \u03ac\u03bb\u03bb\u03b5\u03c2 \u03c4\u03ad\u03c3\u03c3\u03b5\u03c1\u03b9\u03c2 \u03bc\u03ad\u03b8\u03bf\u03b4\u03bf\u03b9 \u03c0\u03bf\u03c5 \u03bc\u03c0\u03cc\u03c1\u03b5\u03c3\u03b1\u03bd \u03bd\u03b1 \u03c3\u03c5\u03b3\u03ba\u03c1\u03b9\u03b8\u03bf\u03cd\u03bd \u03ad\u03b4\u03c9\u03c3\u03b1\u03bd \u03af\u03b4\u03b9\u03b5\u03c2 \u03b5\u03be\u03b7\u03b3\u03ae\u03c3\u03b5\u03b9\u03c2 \u03bc\u03b5 \u03b1\u03bd\u03c4\u03af\u03c3\u03c4\u03bf\u03b9\u03c7\u03b5\u03c2 \u03c0\u03b1\u03c1\u03b1\u03bc\u03ad\u03c4\u03c1\u03bf\u03c5\u03c2, \u03b5\u03bd\u03ce \u03c4\u03bf \u03ba\u03bf\u03b9\u03bd\u03cc ROC-AUC metric \u03ae\u03c4\u03b1\u03bd \u03c3\u03c5\u03bd\u03b5\u03c0\u03ad\u03c2 \u03c3\u03c4\u03b9\u03c2 \u03b4\u03cd\u03bf \u03c5\u03bb\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03b5\u03b9\u03c2 \u03cc\u03c0\u03bf\u03c5 \u03c5\u03c0\u03ae\u03c1\u03c7\u03b5 overlap.<\/p>\n<aside class=\"td-article-note\"><strong>\u0397 \u03b1\u03c3\u03c5\u03bc\u03c6\u03c9\u03bd\u03af\u03b1 \u03ad\u03c7\u03b5\u03b9 \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03bf \u03b5\u03cd\u03c1\u03bf\u03c2:<\/strong> \u03c4\u03bf paper \u03b4\u03b5\u03af\u03c7\u03bd\u03b5\u03b9 \u03cc\u03c4\u03b9 \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03ad\u03c2 implementations \u03bc\u03c0\u03bf\u03c1\u03bf\u03cd\u03bd \u03bd\u03b1 \u03b1\u03c0\u03bf\u03ba\u03bb\u03af\u03bd\u03bf\u03c5\u03bd, \u03cc\u03c7\u03b9 \u03cc\u03c4\u03b9 \u03ba\u03ac\u03b8\u03b5 \u03bc\u03ad\u03b8\u03bf\u03b4\u03bf\u03c2 \u03b1\u03c0\u03bf\u03ba\u03bb\u03af\u03bd\u03b5\u03b9 \u03c0\u03ac\u03bd\u03c4\u03b1. \u0397 cross-framework \u03c3\u03cd\u03b3\u03ba\u03c1\u03b9\u03c3\u03b7 \u03ba\u03ac\u03bb\u03c5\u03c8\u03b5 \u03c0\u03ad\u03bd\u03c4\u03b5 explanation methods \u03ba\u03b1\u03b9 \u03ad\u03bd\u03b1 \u03ba\u03bf\u03b9\u03bd\u03cc metric.<\/aside>\n<p>\u03a4\u03bf \u03b5\u03cd\u03c1\u03b7\u03bc\u03b1 \u03b1\u03c1\u03ba\u03b5\u03af \u03b3\u03b9\u03b1 \u03bd\u03b1 \u03b1\u03bb\u03bb\u03ac\u03be\u03b5\u03b9 \u03c4\u03bf release process. \u0397 \u03b2\u03b9\u03b2\u03bb\u03b9\u03bf\u03b8\u03ae\u03ba\u03b7 \u03ba\u03b1\u03b9 \u03b7 \u03ad\u03ba\u03b4\u03bf\u03c3\u03ae \u03c4\u03b7\u03c2 \u03b5\u03af\u03bd\u03b1\u03b9 \u03bc\u03ad\u03c1\u03bf\u03c2 \u03c4\u03b7\u03c2 \u03c4\u03b1\u03c5\u03c4\u03cc\u03c4\u03b7\u03c4\u03b1\u03c2 \u03c4\u03b7\u03c2 \u03b5\u03be\u03ae\u03b3\u03b7\u03c3\u03b7\u03c2, \u03cc\u03c0\u03c9\u03c2 \u03b5\u03af\u03bd\u03b1\u03b9 \u03ba\u03b1\u03b9 \u03c4\u03bf model checkpoint. \u03a4\u03bf prediction regression \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03c0\u03b5\u03c1\u03bd\u03ac \u03b5\u03bd\u03ce \u03c4\u03bf explanation regression \u03b1\u03c0\u03bf\u03c4\u03c5\u03b3\u03c7\u03ac\u03bd\u03b5\u03b9. \u0397 \u03af\u03b4\u03b9\u03b1 \u03bb\u03bf\u03b3\u03b9\u03ba\u03ae \u03b2\u03c1\u03af\u03c3\u03ba\u03b5\u03c4\u03b1\u03b9 \u03c0\u03af\u03c3\u03c9 \u03b1\u03c0\u03cc \u03ad\u03bd\u03b1 <a href=\"https:\/\/twodots.gr\/airep-apodeiktiko-apofaseon-ai-runtime\/\">\u03b1\u03c0\u03bf\u03b4\u03b5\u03b9\u03ba\u03c4\u03b9\u03ba\u03cc \u03b3\u03b9\u03b1 \u03b1\u03c0\u03bf\u03c6\u03ac\u03c3\u03b5\u03b9\u03c2 AI runtime<\/a>: \u03c7\u03c9\u03c1\u03af\u03c2 provenance \u03ba\u03b1\u03b9 \u03c3\u03c5\u03b3\u03ba\u03c1\u03af\u03c3\u03b9\u03bc\u03b1 artifacts, \u03b7 \u03bf\u03bc\u03ac\u03b4\u03b1 \u03b4\u03b5\u03bd \u03b3\u03bd\u03c9\u03c1\u03af\u03b6\u03b5\u03b9 \u03c4\u03b9 \u03b1\u03ba\u03c1\u03b9\u03b2\u03ce\u03c2 \u03ac\u03bb\u03bb\u03b1\u03be\u03b5.<\/p>\n<h2 id=\"provenance-governance\">\u03a4\u03b9 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03ba\u03b1\u03c4\u03b1\u03b3\u03c1\u03ac\u03c6\u03b5\u03b9 \u03bc\u03b9\u03b1 \u03b5\u03c0\u03b9\u03c7\u03b5\u03af\u03c1\u03b7\u03c3\u03b7<\/h2>\n<p>\u039a\u03ac\u03b8\u03b5 explanation artifact \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03c3\u03c5\u03bd\u03b4\u03ad\u03b5\u03c4\u03b1\u03b9 \u03bc\u03b5 model version, dataset snapshot, framework \u03ba\u03b1\u03b9 version, \u03bc\u03ad\u03b8\u03bf\u03b4\u03bf, baseline, preprocessing, windowing, parameters, metric configuration \u03ba\u03b1\u03b9 execution environment. \u03a7\u03c9\u03c1\u03af\u03c2 \u03b1\u03c5\u03c4\u03ac, \u03bc\u03b9\u03b1 \u03bf\u03bc\u03ac\u03b4\u03b1 \u03b4\u03b5\u03bd \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b1\u03bd\u03b1\u03c0\u03b1\u03c1\u03ac\u03b3\u03b5\u03b9 \u03c4\u03b7\u03bd \u03b5\u03be\u03ae\u03b3\u03b7\u03c3\u03b7 \u03bf\u03cd\u03c4\u03b5 \u03bd\u03b1 \u03b5\u03be\u03b7\u03b3\u03ae\u03c3\u03b5\u03b9 \u03b3\u03b9\u03b1\u03c4\u03af \u03bc\u03b5\u03c4\u03b1\u03ba\u03b9\u03bd\u03ae\u03b8\u03b7\u03ba\u03b5 \u03bc\u03b5\u03c4\u03ac \u03b1\u03c0\u03cc \u03b1\u03bd\u03b1\u03b2\u03ac\u03b8\u03bc\u03b9\u03c3\u03b7.<\/p>\n<p>\u03a7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03b5\u03c0\u03af\u03c3\u03b7\u03c2 test suite \u03b3\u03b9\u03b1 explanations. \u0388\u03bd\u03b1 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b4\u03b9\u03b1\u03c4\u03b7\u03c1\u03b5\u03af accuracy \u03ae F1 \u03bc\u03b5\u03c4\u03ac \u03b1\u03c0\u03cc \u03b1\u03bb\u03bb\u03b1\u03b3\u03ae \u03b2\u03b9\u03b2\u03bb\u03b9\u03bf\u03b8\u03ae\u03ba\u03b7\u03c2, \u03b5\u03bd\u03ce \u03bf\u03b9 \u03c0\u03b5\u03c1\u03b9\u03bf\u03c7\u03ad\u03c2 relevance \u03b1\u03bb\u03bb\u03ac\u03b6\u03bf\u03c5\u03bd. \u03a4\u03b1 regression tests \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b5\u03bb\u03ad\u03b3\u03c7\u03bf\u03c5\u03bd stability, overlap \u03ae \u03ac\u03bb\u03bb\u03bf domain-appropriate \u03ba\u03c1\u03b9\u03c4\u03ae\u03c1\u03b9\u03bf \u03ba\u03b1\u03b9 \u03bd\u03b1 \u03ad\u03c7\u03bf\u03c5\u03bd thresholds \u03c0\u03bf\u03c5 \u03b5\u03b3\u03ba\u03c1\u03af\u03b8\u03b7\u03ba\u03b1\u03bd \u03c0\u03c1\u03b9\u03bd \u03b1\u03c0\u03cc \u03c4\u03bf release, \u03cc\u03c7\u03b9 \u03b1\u03c6\u03bf\u03cd \u03b5\u03bc\u03c6\u03b1\u03bd\u03b9\u03c3\u03c4\u03b5\u03af \u03b7 \u03b1\u03c0\u03cc\u03ba\u03bb\u03b9\u03c3\u03b7.<\/p>\n<p>\u0397 \u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03c4\u03b1\u03b9\u03c1\u03b9\u03ac\u03b6\u03b5\u03b9 \u03c3\u03c4\u03bf domain. \u0393\u03b9\u03b1 \u03c0\u03bf\u03bb\u03c5\u03ba\u03b1\u03bd\u03b1\u03bb\u03b9\u03ba\u03cc ECG, \u03ad\u03bd\u03b1 heatmap \u03c0\u03bf\u03c5 \u03b1\u03b3\u03bd\u03bf\u03b5\u03af cross-channel dependencies \u03b5\u03af\u03bd\u03b1\u03b9 \u03b1\u03bd\u03b5\u03c0\u03b1\u03c1\u03ba\u03ad\u03c2 \u03c9\u03c2 \u03bc\u03bf\u03bd\u03b1\u03b4\u03b9\u03ba\u03cc \u03c4\u03b5\u03ba\u03bc\u03ae\u03c1\u03b9\u03bf. \u0393\u03b9\u03b1 \u03ae\u03c7\u03bf \u03ae \u03b4\u03bf\u03bd\u03ae\u03c3\u03b5\u03b9\u03c2, \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b5\u03be\u03b5\u03c4\u03b1\u03c3\u03c4\u03b5\u03af \u03b1\u03bd \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 frequency-domain explanation. \u0393\u03b9\u03b1 real-time scoring, \u03b7 \u03b5\u03be\u03ae\u03b3\u03b7\u03c3\u03b7 \u03b4\u03b5\u03bd \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03b5\u03af \u03bc\u03b5\u03bb\u03bb\u03bf\u03bd\u03c4\u03b9\u03ba\u03ac \u03c3\u03b7\u03bc\u03b5\u03af\u03b1.<\/p>\n<p>\u03a4\u03bf XAI \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03b1\u03c5\u03c4\u03cc\u03bc\u03b1\u03c4\u03b7 \u03b1\u03c0\u03cc\u03b4\u03b5\u03b9\u03be\u03b7 \u03c3\u03c5\u03bc\u03bc\u03cc\u03c1\u03c6\u03c9\u03c3\u03b7\u03c2. \u03a4\u03bf \u03ac\u03c1\u03b8\u03c1\u03bf 14 \u03c4\u03bf\u03c5 \u03b5\u03c5\u03c1\u03c9\u03c0\u03b1\u03ca\u03ba\u03bf\u03cd AI Act \u03b8\u03ad\u03c4\u03b5\u03b9 \u03b1\u03c0\u03b1\u03b9\u03c4\u03ae\u03c3\u03b5\u03b9\u03c2 \u03b1\u03bd\u03b8\u03c1\u03ce\u03c0\u03b9\u03bd\u03b7\u03c2 \u03b5\u03c0\u03bf\u03c0\u03c4\u03b5\u03af\u03b1\u03c2 \u03b3\u03b9\u03b1 high-risk AI, \u03b1\u03bb\u03bb\u03ac \u03c4\u03bf \u03b1\u03bd \u03ba\u03b1\u03b9 \u03c0\u03ce\u03c2 \u03b5\u03c6\u03b1\u03c1\u03bc\u03cc\u03b6\u03b5\u03c4\u03b1\u03b9 \u03b5\u03be\u03b1\u03c1\u03c4\u03ac\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc \u03c4\u03bf \u03c3\u03cd\u03c3\u03c4\u03b7\u03bc\u03b1 \u03ba\u03b1\u03b9 \u03b1\u03c0\u03b1\u03b9\u03c4\u03b5\u03af \u03bd\u03bf\u03bc\u03b9\u03ba\u03ae \u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7. \u0388\u03bd\u03b1 explanation interface \u03b4\u03b5\u03bd \u03b1\u03c1\u03ba\u03b5\u03af \u03b1\u03c0\u03cc \u03bc\u03cc\u03bd\u03bf \u03c4\u03bf\u03c5: \u03bf \u03ac\u03bd\u03b8\u03c1\u03c9\u03c0\u03bf\u03c2 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03ba\u03b1\u03c4\u03b1\u03bd\u03bf\u03b5\u03af \u03c4\u03b9\u03c2 \u03b4\u03c5\u03bd\u03b1\u03c4\u03cc\u03c4\u03b7\u03c4\u03b5\u03c2 \u03ba\u03b1\u03b9 \u03c4\u03b1 \u03cc\u03c1\u03b9\u03b1, \u03bd\u03b1 \u03b5\u03bd\u03c4\u03bf\u03c0\u03af\u03b6\u03b5\u03b9 anomalies, \u03bd\u03b1 \u03b1\u03c0\u03bf\u03c6\u03b5\u03cd\u03b3\u03b5\u03b9 automation bias \u03ba\u03b1\u03b9 \u03bd\u03b1 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b1\u03b3\u03bd\u03bf\u03ae\u03c3\u03b5\u03b9, \u03b1\u03bd\u03b1\u03c3\u03c4\u03c1\u03ad\u03c8\u03b5\u03b9 \u03ae \u03b4\u03b9\u03b1\u03ba\u03cc\u03c8\u03b5\u03b9 \u03c4\u03bf \u03c3\u03cd\u03c3\u03c4\u03b7\u03bc\u03b1 \u03cc\u03c0\u03bf\u03c5 \u03b1\u03c0\u03b1\u03b9\u03c4\u03b5\u03af\u03c4\u03b1\u03b9. \u0391\u03c5\u03c4\u03cc \u03b5\u03af\u03bd\u03b1\u03b9 \u03c4\u03bf \u03bf\u03c5\u03c3\u03b9\u03b1\u03c3\u03c4\u03b9\u03ba\u03cc \u03c0\u03ad\u03c1\u03b1\u03c3\u03bc\u03b1 <a href=\"https:\/\/twodots.gr\/apo-ton-anthropo-ston-brocho-sten-pragmatike-anthropine-exousia-sten-technete-noemosyne\/\">\u03b1\u03c0\u03cc \u03c4\u03bf\u03bd \u03ac\u03bd\u03b8\u03c1\u03c9\u03c0\u03bf \u03c3\u03c4\u03bf\u03bd \u03b2\u03c1\u03cc\u03c7\u03bf \u03c3\u03c4\u03b7\u03bd \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ae \u03b1\u03bd\u03b8\u03c1\u03ce\u03c0\u03b9\u03bd\u03b7 \u03b5\u03be\u03bf\u03c5\u03c3\u03af\u03b1<\/a>.<\/p>\n<div class=\"td-decision-band\">\n<p class=\"td-decision-kicker\">Release gate \u03b3\u03b9\u03b1 \u03b5\u03be\u03b7\u03b3\u03ae\u03c3\u03b5\u03b9\u03c2<\/p>\n<p class=\"td-decision-title\">\u0391\u03bd \u03b1\u03bb\u03bb\u03ac\u03be\u03b5\u03b9 framework, \u03ad\u03ba\u03b4\u03bf\u03c3\u03b7 \u03ae preprocessing, \u03be\u03b1\u03bd\u03b1\u03bc\u03b5\u03c4\u03c1\u03ae\u03c3\u03c4\u03b5 \u03c4\u03bf explanation pipeline<\/p>\n<p>\u03a0\u03b1\u03b3\u03ce\u03c3\u03c4\u03b5 \u03c4\u03bf production artifact, \u03c3\u03c5\u03b3\u03ba\u03c1\u03af\u03bd\u03b5\u03c4\u03b5 predictions \u03ba\u03b1\u03b9 explanations \u03c3\u03b5 domain-reviewed cases \u03ba\u03b1\u03b9 \u03ba\u03c1\u03b1\u03c4\u03ae\u03c3\u03c4\u03b5 rollback. \u038a\u03b4\u03b9\u03bf accuracy \u03b4\u03b5\u03bd \u03c3\u03b7\u03bc\u03b1\u03af\u03bd\u03b5\u03b9 \u03af\u03b4\u03b9\u03b1 \u03b1\u03b9\u03c4\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7, \u03b5\u03bd\u03ce \u03ad\u03bd\u03b1 \u03cc\u03bc\u03bf\u03c1\u03c6\u03bf heatmap \u03b4\u03b5\u03bd \u03c5\u03c0\u03bf\u03ba\u03b1\u03b8\u03b9\u03c3\u03c4\u03ac \u03c4\u03b7\u03bd \u03b1\u03bd\u03b1\u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03b9\u03bc\u03cc\u03c4\u03b7\u03c4\u03b1.<\/p>\n<\/div>\n<h2 id=\"epta-vimata-xai-pilot\">\u0395\u03c0\u03c4\u03ac \u03b2\u03ae\u03bc\u03b1\u03c4\u03b1 \u03b3\u03b9\u03b1 \u03b5\u03bb\u03b5\u03b3\u03c7\u03cc\u03bc\u03b5\u03bd\u03bf XAI pilot<\/h2>\n<p>\u0397 explainability \u03b3\u03af\u03bd\u03b5\u03c4\u03b1\u03b9 \u03c7\u03c1\u03ae\u03c3\u03b9\u03bc\u03b7 \u03cc\u03c4\u03b1\u03bd \u03c3\u03c5\u03bd\u03b4\u03ad\u03b5\u03c4\u03b1\u03b9 \u03bc\u03b5 \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03b7 \u03b1\u03c0\u03cc\u03c6\u03b1\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03b1\u03c0\u03bf\u03b4\u03b5\u03ba\u03c4\u03cc failure mode. \u0388\u03bd\u03b1 pilot \u03b4\u03b5\u03bd \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03bd\u03b1 \u03be\u03b5\u03ba\u03b9\u03bd\u03ae\u03c3\u03b5\u03b9 \u03bc\u03b5 \u03cc\u03bb\u03b5\u03c2 \u03c4\u03b9\u03c2 \u03bc\u03b5\u03b8\u03cc\u03b4\u03bf\u03c5\u03c2 \u03c4\u03b7\u03c2 \u03b2\u03b9\u03b2\u03bb\u03b9\u03bf\u03b8\u03ae\u03ba\u03b7\u03c2. \u03a7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03bd\u03b1 \u03be\u03b5\u03ba\u03b9\u03bd\u03ae\u03c3\u03b5\u03b9 \u03bc\u03b5 \u03c3\u03b1\u03c6\u03ae \u03b5\u03c1\u03ce\u03c4\u03b7\u03c3\u03b7, \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ac \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03b1 \u03ba\u03b1\u03b9 \u03ba\u03c1\u03b9\u03c4\u03ae\u03c1\u03b9\u03b1 \u03c0\u03bf\u03c5 \u03b5\u03c0\u03b9\u03c4\u03c1\u03ad\u03c0\u03bf\u03c5\u03bd \u03c3\u03c4\u03b7\u03bd \u03bf\u03bc\u03ac\u03b4\u03b1 \u03bd\u03b1 \u03b1\u03c0\u03bf\u03c1\u03c1\u03af\u03c8\u03b5\u03b9 \u03bc\u03b9\u03b1 \u03c0\u03b5\u03b9\u03c3\u03c4\u03b9\u03ba\u03ae \u03b1\u03bb\u03bb\u03ac \u03bc\u03b7 \u03c0\u03b9\u03c3\u03c4\u03ae \u03b5\u03be\u03ae\u03b3\u03b7\u03c3\u03b7.<\/p>\n<div class=\"td-step-list\">\n<p class=\"td-step-list-title\">\u0391\u03c0\u03cc \u03c4\u03bf use case \u03c3\u03b5 \u03b1\u03bd\u03b1\u03c0\u03b1\u03c1\u03b1\u03b3\u03ce\u03b3\u03b9\u03bc\u03bf explanation pipeline<\/p>\n<ol>\n<li><span class=\"td-step-kicker\">Step 1<\/span><strong>\u039f\u03c1\u03af\u03c3\u03c4\u03b5 \u03c4\u03b7\u03bd \u03b1\u03c0\u03cc\u03c6\u03b1\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03c4\u03bf\u03bd \u03c7\u03c1\u03ae\u03c3\u03c4\u03b7 \u03c4\u03b7\u03c2 \u03b5\u03be\u03ae\u03b3\u03b7\u03c3\u03b7\u03c2<\/strong>\n<p>\u039a\u03b1\u03c4\u03b1\u03b3\u03c1\u03ac\u03c8\u03c4\u03b5 \u03b1\u03bd \u03bf reviewer \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03c7\u03c1\u03bf\u03bd\u03b9\u03ba\u03ac \u03c3\u03b7\u03bc\u03b5\u03af\u03b1, \u03c3\u03c5\u03c7\u03bd\u03cc\u03c4\u03b7\u03c4\u03b5\u03c2, \u03c3\u03c7\u03ad\u03c3\u03b5\u03b9\u03c2 \u03ba\u03b1\u03bd\u03b1\u03bb\u03b9\u03ce\u03bd \u03ae counterfactual \u03ba\u03b1\u03b9 \u03c0\u03bf\u03b9\u03b1 \u03b5\u03bd\u03ad\u03c1\u03b3\u03b5\u03b9\u03b1 \u03b8\u03b1 \u03c0\u03ac\u03c1\u03b5\u03b9 \u03bc\u03b5 \u03b2\u03ac\u03c3\u03b7 \u03b1\u03c5\u03c4\u03ac.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">Step 2<\/span><strong>\u03a7\u03b1\u03c1\u03c4\u03bf\u03b3\u03c1\u03b1\u03c6\u03ae\u03c3\u03c4\u03b5 \u03c4\u03b7 \u03b4\u03bf\u03bc\u03ae \u03c4\u03bf\u03c5 \u03c3\u03ae\u03bc\u03b1\u03c4\u03bf\u03c2<\/strong>\n<p>\u0394\u03b7\u03bb\u03ce\u03c3\u03c4\u03b5 sampling rate, \u03bc\u03ae\u03ba\u03bf\u03c2 \u03c0\u03b1\u03c1\u03b1\u03b8\u03cd\u03c1\u03bf\u03c5, preprocessing, \u03b4\u03b9\u03b1\u03b8\u03ad\u03c3\u03b9\u03bc\u03b1 \u03ba\u03b1\u03bd\u03ac\u03bb\u03b9\u03b1, \u03c0\u03b9\u03b8\u03b1\u03bd\u03ae leakage \u03b1\u03c0\u03cc \u03c4\u03bf \u03bc\u03ad\u03bb\u03bb\u03bf\u03bd \u03ba\u03b1\u03b9 \u03b1\u03bd \u03c4\u03bf frequency domain \u03c6\u03ad\u03c1\u03b5\u03b9 \u03b5\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03b7\u03c3\u03b9\u03b1\u03ba\u03ae \u03c3\u03b7\u03bc\u03b1\u03c3\u03af\u03b1.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">Step 3<\/span><strong>\u0395\u03c0\u03b9\u03bb\u03ad\u03be\u03c4\u03b5 method \u03ba\u03b1\u03b9 framework \u03bc\u03b1\u03b6\u03af<\/strong>\n<p>\u039c\u03b7\u03bd \u03c0\u03c1\u03bf\u03bc\u03b7\u03b8\u03b5\u03cd\u03b5\u03c3\u03c4\u03b5 \u03bc\u03b9\u03b1 \u03b1\u03c6\u03b7\u03c1\u03b7\u03bc\u03ad\u03bd\u03b7 \u03bf\u03bd\u03bf\u03bc\u03b1\u03c3\u03af\u03b1 \u03cc\u03c0\u03c9\u03c2 Integrated Gradients. \u039a\u03bb\u03b5\u03b9\u03b4\u03ce\u03c3\u03c4\u03b5 library, version, backend, baseline, interpolation steps \u03ba\u03b1\u03b9 \u03cc\u03bb\u03b5\u03c2 \u03c4\u03b9\u03c2 default \u03c0\u03b1\u03c1\u03b1\u03bc\u03ad\u03c4\u03c1\u03bf\u03c5\u03c2.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">Step 4<\/span><strong>\u03a7\u03c4\u03af\u03c3\u03c4\u03b5 domain-reviewed reference cases<\/strong>\n<p>\u03a3\u03c5\u03bd\u03b4\u03c5\u03ac\u03c3\u03c4\u03b5 synthetic ground truth \u03bc\u03b5 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ac \u03c0\u03b5\u03c1\u03b9\u03c3\u03c4\u03b1\u03c4\u03b9\u03ba\u03ac \u03c0\u03bf\u03c5 \u03ad\u03c7\u03bf\u03c5\u03bd \u03b5\u03bb\u03b5\u03b3\u03c7\u03b8\u03b5\u03af \u03b1\u03c0\u03cc \u03b5\u03b9\u03b4\u03b9\u03ba\u03bf\u03cd\u03c2 \u03ba\u03b1\u03b9 \u03c0\u03b5\u03c1\u03b9\u03bb\u03b1\u03bc\u03b2\u03ac\u03bd\u03bf\u03c5\u03bd \u03b4\u03cd\u03c3\u03ba\u03bf\u03bb\u03b1, \u03bf\u03c1\u03b9\u03b1\u03ba\u03ac \u03ba\u03b1\u03b9 \u03b1\u03c0\u03bf\u03c4\u03c5\u03c7\u03b7\u03bc\u03ad\u03bd\u03b1 predictions.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">Step 5<\/span><strong>\u039c\u03b5\u03c4\u03c1\u03ae\u03c3\u03c4\u03b5 fidelity \u03ba\u03b1\u03b9 stability \u03c7\u03c9\u03c1\u03b9\u03c3\u03c4\u03ac<\/strong>\n<p>\u0395\u03bb\u03ad\u03b3\u03be\u03c4\u03b5 \u03b1\u03bd \u03b7 \u03b5\u03be\u03ae\u03b3\u03b7\u03c3\u03b7 \u03b1\u03bd\u03c4\u03b1\u03bd\u03b1\u03ba\u03bb\u03ac \u03c4\u03b7 \u03c3\u03c5\u03bc\u03c0\u03b5\u03c1\u03b9\u03c6\u03bf\u03c1\u03ac \u03c4\u03bf\u03c5 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf\u03c5 \u03ba\u03b1\u03b9 \u03b1\u03bd \u03c0\u03b1\u03c1\u03b1\u03bc\u03ad\u03bd\u03b5\u03b9 \u03b1\u03c1\u03ba\u03b5\u03c4\u03ac \u03c3\u03c4\u03b1\u03b8\u03b5\u03c1\u03ae \u03c3\u03b5 seeds, \u03bc\u03b9\u03ba\u03c1\u03ad\u03c2 \u03bc\u03b5\u03c4\u03b1\u03b2\u03bf\u03bb\u03ad\u03c2, machines \u03ba\u03b1\u03b9 dependency updates.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">Step 6<\/span><strong>\u03a0\u03c1\u03bf\u03c3\u03b8\u03ad\u03c3\u03c4\u03b5 cross-implementation check<\/strong>\n<p>\u0393\u03b9\u03b1 \u03ba\u03c1\u03af\u03c3\u03b9\u03bc\u03b1 use cases, \u03c3\u03c5\u03b3\u03ba\u03c1\u03af\u03bd\u03b5\u03c4\u03b5 \u03b4\u03b5\u03cd\u03c4\u03b5\u03c1\u03b7 implementation \u03cc\u03c0\u03bf\u03c5 \u03c5\u03c0\u03ac\u03c1\u03c7\u03b5\u03b9 \u03ba\u03b1\u03b9 \u03b5\u03c1\u03b5\u03c5\u03bd\u03ae\u03c3\u03c4\u03b5 \u03ba\u03ac\u03b8\u03b5 \u03c3\u03c5\u03c3\u03c4\u03b7\u03bc\u03b1\u03c4\u03b9\u03ba\u03ae \u03b1\u03c0\u03cc\u03ba\u03bb\u03b9\u03c3\u03b7 \u03c0\u03c1\u03b9\u03bd \u03b5\u03c0\u03b9\u03c4\u03c1\u03ad\u03c8\u03b5\u03c4\u03b5 release.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">Step 7<\/span><strong>\u039a\u03c1\u03b1\u03c4\u03ae\u03c3\u03c4\u03b5 provenance, monitoring \u03ba\u03b1\u03b9 rollback<\/strong>\n<p>\u0391\u03c0\u03bf\u03b8\u03b7\u03ba\u03b5\u03cd\u03c3\u03c4\u03b5 explanation artifacts \u03bc\u03b5 model \u03ba\u03b1\u03b9 data versions, \u03b5\u03c0\u03b1\u03bd\u03b5\u03ba\u03c4\u03b5\u03bb\u03ad\u03c3\u03c4\u03b5 \u03c4\u03bf suite \u03c3\u03b5 \u03ba\u03ac\u03b8\u03b5 \u03b1\u03bb\u03bb\u03b1\u03b3\u03ae \u03ba\u03b1\u03b9 \u03b5\u03c0\u03b9\u03c3\u03c4\u03c1\u03ad\u03c8\u03c4\u03b5 \u03c3\u03c4\u03b7\u03bd \u03c0\u03c1\u03bf\u03b7\u03b3\u03bf\u03cd\u03bc\u03b5\u03bd\u03b7 \u03ad\u03ba\u03b4\u03bf\u03c3\u03b7 \u03b1\u03bd \u03c3\u03c0\u03ac\u03c3\u03bf\u03c5\u03bd \u03c4\u03b1 \u03b5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03b1 \u03cc\u03c1\u03b9\u03b1.<\/p>\n<\/li>\n<\/ol>\n<\/div>\n<p>\u0397 \u03b4\u03b9\u03b1\u03b4\u03b9\u03ba\u03b1\u03c3\u03af\u03b1 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b5\u03bd\u03c3\u03c9\u03bc\u03b1\u03c4\u03c9\u03b8\u03b5\u03af \u03c3\u03b5 MLOps \u03ae \u03c3\u03b5 \u03b5\u03c5\u03c1\u03cd\u03c4\u03b5\u03c1\u03bf\u03c5\u03c2 <a href=\"https:\/\/twodots.gr\/aftomatismoi-epicheiriseon-ai\/\">\u03b1\u03c5\u03c4\u03bf\u03bc\u03b1\u03c4\u03b9\u03c3\u03bc\u03bf\u03cd\u03c2 \u03b5\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03ae\u03c3\u03b5\u03c9\u03bd \u03ba\u03b1\u03b9 AI<\/a>, \u03b1\u03c1\u03ba\u03b5\u03af \u03c4\u03b1 gates \u03bd\u03b1 \u03bc\u03b7 \u03bc\u03b5\u03c4\u03b1\u03c4\u03c1\u03b1\u03c0\u03bf\u03cd\u03bd \u03c3\u03b5 \u03c4\u03c5\u03c0\u03b9\u03ba\u03ac checkboxes. Prediction quality, explanation quality, human usability \u03ba\u03b1\u03b9 operational risk \u03b5\u03af\u03bd\u03b1\u03b9 \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03ac \u03c0\u03b5\u03b4\u03af\u03b1 \u03b5\u03bb\u03ad\u03b3\u03c7\u03bf\u03c5.<\/p>\n<h2 id=\"periorismoi-symperasma\">\u03a0\u03b5\u03c1\u03b9\u03bf\u03c1\u03b9\u03c3\u03bc\u03bf\u03af \u03ba\u03b1\u03b9 \u03c0\u03c1\u03b1\u03ba\u03c4\u03b9\u03ba\u03cc \u03c3\u03c5\u03bc\u03c0\u03ad\u03c1\u03b1\u03c3\u03bc\u03b1<\/h2>\n<p>\u0397 \u03b1\u03bd\u03b1\u03c3\u03ba\u03cc\u03c0\u03b7\u03c3\u03b7 \u03b5\u03c3\u03c4\u03b9\u03ac\u03b6\u03b5\u03b9 \u03c3\u03b5 time-series classification. \u039f\u03b9 \u03af\u03b4\u03b9\u03bf\u03b9 \u03bf\u03b9 \u03c3\u03c5\u03b3\u03b3\u03c1\u03b1\u03c6\u03b5\u03af\u03c2 \u03c3\u03b7\u03bc\u03b5\u03b9\u03ce\u03bd\u03bf\u03c5\u03bd \u03cc\u03c4\u03b9 forecasting \u03ba\u03b1\u03b9 anomaly detection \u03b5\u03af\u03bd\u03b1\u03b9 \u03b1\u03ba\u03cc\u03bc\u03b7 \u03bb\u03b9\u03b3\u03cc\u03c4\u03b5\u03c1\u03bf \u03bc\u03b5\u03bb\u03b5\u03c4\u03b7\u03bc\u03ad\u03bd\u03b1 \u03b1\u03c0\u03cc \u03c0\u03bb\u03b5\u03c5\u03c1\u03ac\u03c2 XAI, \u03c0\u03b1\u03c1\u03cc\u03c4\u03b9 \u03ad\u03c7\u03bf\u03c5\u03bd \u03bc\u03b5\u03b3\u03ac\u03bb\u03b7 \u03c0\u03c1\u03b1\u03ba\u03c4\u03b9\u03ba\u03ae \u03c3\u03b7\u03bc\u03b1\u03c3\u03af\u03b1. \u0395\u03c0\u03bf\u03bc\u03ad\u03bd\u03c9\u03c2 \u03c4\u03b1 \u03b5\u03c5\u03c1\u03ae\u03bc\u03b1\u03c4\u03b1 \u03b4\u03b5\u03bd \u03b1\u03c0\u03bf\u03c4\u03b5\u03bb\u03bf\u03cd\u03bd \u03ad\u03c4\u03bf\u03b9\u03bc\u03b7 \u03c0\u03b9\u03c3\u03c4\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7 \u03b3\u03b9\u03b1 \u03ba\u03ac\u03b8\u03b5 \u03b5\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03b7\u03c3\u03b9\u03b1\u03ba\u03cc use case.<\/p>\n<p>\u0397 \u03b1\u03bd\u03b1\u03b6\u03ae\u03c4\u03b7\u03c3\u03b7 \u03c0\u03b5\u03c1\u03b9\u03bf\u03c1\u03af\u03c3\u03c4\u03b7\u03ba\u03b5 \u03c3\u03c4\u03bf GitHub \u03ba\u03b1\u03b9 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03ad\u03c7\u03b1\u03c3\u03b5 \u03b5\u03c1\u03b3\u03b1\u03bb\u03b5\u03af\u03b1 \u03c3\u03b5 \u03ac\u03bb\u03bb\u03b5\u03c2 \u03c0\u03bb\u03b1\u03c4\u03c6\u03cc\u03c1\u03bc\u03b5\u03c2. \u0397 \u03c3\u03cd\u03b3\u03ba\u03c1\u03b9\u03c3\u03b7 \u03b1\u03bd\u03b1\u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03b9\u03bc\u03cc\u03c4\u03b7\u03c4\u03b1\u03c2 \u03ba\u03ac\u03bb\u03c5\u03c8\u03b5 \u03bc\u03cc\u03bd\u03bf \u03c0\u03ad\u03bd\u03c4\u03b5 \u03bc\u03b5\u03b8\u03cc\u03b4\u03bf\u03c5\u03c2 \u03ba\u03b1\u03b9 \u03ad\u03bd\u03b1 metric \u03c0\u03bf\u03c5 \u03c5\u03c0\u03ae\u03c1\u03c7\u03b1\u03bd \u03c3\u03b5 \u03c0\u03b5\u03c1\u03b9\u03c3\u03c3\u03cc\u03c4\u03b5\u03c1\u03b5\u03c2 \u03b1\u03c0\u03cc \u03bc\u03af\u03b1 implementations. \u03a4\u03b1 \u03b1\u03c0\u03bf\u03c4\u03b5\u03bb\u03ad\u03c3\u03bc\u03b1\u03c4\u03b1 \u03b1\u03c0\u03bf\u03b4\u03b5\u03b9\u03ba\u03bd\u03cd\u03bf\u03c5\u03bd \u03cc\u03c4\u03b9 \u03b7 \u03b1\u03c3\u03c5\u03bc\u03c6\u03c9\u03bd\u03af\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b4\u03c5\u03bd\u03b1\u03c4\u03ae \u03ba\u03b1\u03b9 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c3\u03c5\u03c3\u03c4\u03b7\u03bc\u03b1\u03c4\u03b9\u03ba\u03ae, \u03cc\u03c7\u03b9 \u03c0\u03cc\u03c3\u03bf \u03c3\u03c5\u03c7\u03bd\u03ae \u03b5\u03af\u03bd\u03b1\u03b9 \u03c3\u03b5 \u03bf\u03bb\u03cc\u03ba\u03bb\u03b7\u03c1\u03bf \u03c4\u03bf \u03c0\u03b5\u03b4\u03af\u03bf.<\/p>\n<p>\u03a0\u03b1\u03c1\u03ac \u03c4\u03bf\u03c5\u03c2 \u03c0\u03b5\u03c1\u03b9\u03bf\u03c1\u03b9\u03c3\u03bc\u03bf\u03cd\u03c2, \u03b7 \u03b5\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03b7\u03c3\u03b9\u03b1\u03ba\u03ae \u03ba\u03b1\u03c4\u03b5\u03cd\u03b8\u03c5\u03bd\u03c3\u03b7 \u03b5\u03af\u03bd\u03b1\u03b9 \u03ba\u03b1\u03b8\u03b1\u03c1\u03ae. \u0397 \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ae \u03b4\u03b7\u03bc\u03bf\u03c6\u03b9\u03bb\u03bf\u03cd\u03c2 framework \u03b4\u03b5\u03bd \u03b5\u03b3\u03b3\u03c5\u03ac\u03c4\u03b1\u03b9 \u03cc\u03c4\u03b9 \u03b7 \u03b5\u03be\u03ae\u03b3\u03b7\u03c3\u03b7 \u03b5\u03af\u03bd\u03b1\u03b9 \u03ba\u03b1\u03c4\u03ac\u03bb\u03bb\u03b7\u03bb\u03b7 \u03b3\u03b9\u03b1 \u03c7\u03c1\u03bf\u03bd\u03bf\u03c3\u03b5\u03b9\u03c1\u03ad\u03c2 \u03ae \u03cc\u03c4\u03b9 \u03b8\u03b1 \u03b1\u03bd\u03b1\u03c0\u03b1\u03c1\u03b1\u03c7\u03b8\u03b5\u03af \u03b1\u03bb\u03bb\u03bf\u03cd. \u03a4\u03bf explanation pipeline \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b1\u03be\u03b9\u03bf\u03bb\u03bf\u03b3\u03b5\u03af\u03c4\u03b1\u03b9 \u03cc\u03c0\u03c9\u03c2 \u03c4\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf: \u03bc\u03b5 versions, domain-appropriate tests, reference cases, monitoring \u03ba\u03b1\u03b9 \u03c3\u03b1\u03c6\u03ad\u03c2 rollback.<\/p>\n<p>\u0397 \u03bf\u03c5\u03c3\u03b9\u03b1\u03c3\u03c4\u03b9\u03ba\u03ae explainability \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 screenshot. \u0395\u03af\u03bd\u03b1\u03b9 \u03b5\u03c0\u03b1\u03bd\u03b1\u03bb\u03ae\u03c8\u03b9\u03bc\u03b7 \u03b4\u03b9\u03b1\u03b4\u03b9\u03ba\u03b1\u03c3\u03af\u03b1 \u03bc\u03b5 \u03ba\u03b1\u03c4\u03b1\u03b3\u03b5\u03b3\u03c1\u03b1\u03bc\u03bc\u03ad\u03bd\u03b5\u03c2 \u03c5\u03c0\u03bf\u03b8\u03ad\u03c3\u03b5\u03b9\u03c2, \u03c4\u03b5\u03c7\u03bd\u03b9\u03ba\u03ac \u03af\u03c7\u03bd\u03b7, domain expertise \u03ba\u03b1\u03b9 \u03b4\u03b7\u03bb\u03c9\u03bc\u03ad\u03bd\u03b1 \u03cc\u03c1\u03b9\u03b1. \u038c\u03c4\u03b1\u03bd \u03b1\u03c5\u03c4\u03ac \u03bb\u03b5\u03af\u03c0\u03bf\u03c5\u03bd, \u03c4\u03bf \u03af\u03b4\u03b9\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b4\u03b9\u03b1\u03c4\u03b7\u03c1\u03b5\u03af \u03c4\u03b7\u03bd \u03c0\u03c1\u03cc\u03b2\u03bb\u03b5\u03c8\u03ae \u03c4\u03bf\u03c5 \u03b1\u03bb\u03bb\u03ac \u03bd\u03b1 \u03b1\u03bb\u03bb\u03ac\u03b6\u03b5\u03b9 \u03c4\u03b7\u03bd \u03b9\u03c3\u03c4\u03bf\u03c1\u03af\u03b1 \u03c0\u03bf\u03c5 \u03bb\u03ad\u03b5\u03b9 \u03b3\u03b9\u03b1 \u03b1\u03c5\u03c4\u03ae.<\/p>\n<section class=\"td-service-cta\">\n<div class=\"td-service-cta-content\">\n<p class=\"td-service-cta-kicker\">AI analytics \u03bc\u03b5 \u03b5\u03bb\u03b5\u03b3\u03c7\u03cc\u03bc\u03b5\u03bd\u03b5\u03c2 \u03b5\u03be\u03b7\u03b3\u03ae\u03c3\u03b5\u03b9\u03c2<\/p>\n<p class=\"td-service-cta-title\">\u039c\u03b5\u03c4\u03b1\u03c4\u03c1\u03ad\u03c8\u03c4\u03b5 \u03c4\u03bf XAI \u03b1\u03c0\u03cc heatmap \u03c3\u03b5 \u03bc\u03b5\u03c4\u03c1\u03ae\u03c3\u03b9\u03bc\u03bf production pipeline<\/p>\n<p>\u0397 TWO DOTS \u03c3\u03c7\u03b5\u03b4\u03b9\u03ac\u03b6\u03b5\u03b9 \u03b5\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03b7\u03c3\u03b9\u03b1\u03ba\u03ac AI workflows \u03bc\u03b5 data provenance, evaluation gates, monitoring, \u03b1\u03c3\u03c6\u03b1\u03bb\u03ae rollbacks \u03ba\u03b1\u03b9 \u03b1\u03bd\u03b8\u03c1\u03ce\u03c0\u03b9\u03bd\u03b7 \u03b5\u03c0\u03bf\u03c0\u03c4\u03b5\u03af\u03b1 \u03b3\u03b9\u03b1 time-series analytics \u03ba\u03b1\u03b9 \u03b1\u03c5\u03c4\u03bf\u03bc\u03b1\u03c4\u03b9\u03c3\u03bc\u03bf\u03cd\u03c2.<\/p>\n<div class=\"td-service-cta-actions\"><a class=\"td-service-cta-button\" href=\"https:\/\/twodots.gr\/aftomatismoi-epicheiriseon-ai\/\">\u0394\u03b5\u03af\u03c4\u03b5 \u03bb\u03cd\u03c3\u03b5\u03b9\u03c2 \u03b1\u03c5\u03c4\u03bf\u03bc\u03b1\u03c4\u03b9\u03c3\u03bc\u03ce\u03bd \u03ba\u03b1\u03b9 AI<\/a><\/div>\n<\/div>\n<\/section>\n<section id=\"sychnes-erotiseis\" class=\"td-faq-section\">\n<div class=\"td-faq\">\n<p class=\"td-faq-heading\">Frequently Asked Questions (FAQs)<\/p>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a4\u03b9 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c4\u03bf explainable AI \u03c3\u03c4\u03b9\u03c2 \u03c7\u03c1\u03bf\u03bd\u03bf\u03c3\u03b5\u03b9\u03c1\u03ad\u03c2;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u0395\u03af\u03bd\u03b1\u03b9 \u03bf\u03b9 \u03bc\u03ad\u03b8\u03bf\u03b4\u03bf\u03b9 \u03ba\u03b1\u03b9 \u03bf\u03b9 \u03b4\u03b9\u03b1\u03b4\u03b9\u03ba\u03b1\u03c3\u03af\u03b5\u03c2 \u03c0\u03bf\u03c5 \u03b5\u03be\u03b5\u03c4\u03ac\u03b6\u03bf\u03c5\u03bd \u03c0\u03bf\u03b9\u03b1 \u03c7\u03c1\u03bf\u03bd\u03b9\u03ba\u03ac \u03c3\u03b7\u03bc\u03b5\u03af\u03b1, features, \u03ba\u03b1\u03bd\u03ac\u03bb\u03b9\u03b1 \u03ae \u03b1\u03bd\u03b1\u03c0\u03b1\u03c1\u03b1\u03c3\u03c4\u03ac\u03c3\u03b5\u03b9\u03c2 \u03c3\u03c5\u03bd\u03ad\u03b2\u03b1\u03bb\u03b1\u03bd \u03c3\u03b5 \u03c0\u03c1\u03cc\u03b2\u03bb\u03b5\u03c8\u03b7 \u03c0\u03ac\u03bd\u03c9 \u03c3\u03b5 \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03b1 \u03bc\u03b5 \u03c7\u03c1\u03bf\u03bd\u03b9\u03ba\u03ae \u03c3\u03b5\u03b9\u03c1\u03ac.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a0\u03bf\u03b9\u03b1 \u03ad\u03be\u03b9 frameworks \u03b5\u03be\u03ad\u03c4\u03b1\u03c3\u03b5 \u03b7 \u03b1\u03bd\u03b1\u03c3\u03ba\u03cc\u03c0\u03b7\u03c3\u03b7;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u03a4\u03b1 TSInterpret, tsCaptum, SIGN-XAI-2, Quantus, time_interpret \u03ba\u03b1\u03b9 XTSC-Bench.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a0\u03cc\u03c3\u03b5\u03c2 \u03bc\u03ad\u03b8\u03bf\u03b4\u03bf\u03b9 \u03ae\u03c4\u03b1\u03bd \u03c3\u03c7\u03b5\u03b4\u03b9\u03b1\u03c3\u03bc\u03ad\u03bd\u03b5\u03c2 \u03b5\u03b9\u03b4\u03b9\u03ba\u03ac \u03b3\u03b9\u03b1 \u03c7\u03c1\u03bf\u03bd\u03bf\u03c3\u03b5\u03b9\u03c1\u03ad\u03c2;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u0391\u03c0\u03cc \u03c4\u03b9\u03c2 51 \u03bc\u03b5\u03b8\u03cc\u03b4\u03bf\u03c5\u03c2 \u03c0\u03bf\u03c5 \u03ba\u03b1\u03c4\u03b1\u03b3\u03c1\u03ac\u03c6\u03b7\u03ba\u03b1\u03bd, \u03bc\u03cc\u03bd\u03bf 16 \u03b4\u03ae\u03bb\u03c9\u03bd\u03b1\u03bd \u03c1\u03b7\u03c4\u03ac \u03cc\u03c4\u03b9 \u03b1\u03bd\u03b1\u03c0\u03c4\u03cd\u03c7\u03b8\u03b7\u03ba\u03b1\u03bd \u03b3\u03b9\u03b1 \u03c7\u03c1\u03bf\u03bd\u03bf\u03c3\u03b5\u03b9\u03c1\u03ad\u03c2.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u0393\u03b9\u03b1\u03c4\u03af \u03ad\u03c7\u03b5\u03b9 \u03c3\u03b7\u03bc\u03b1\u03c3\u03af\u03b1 \u03c4\u03bf frequency domain;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u03a3\u03b5 \u03ae\u03c7\u03bf, \u03b2\u03b9\u03bf\u03ca\u03b1\u03c4\u03c1\u03b9\u03ba\u03ac \u03c3\u03ae\u03bc\u03b1\u03c4\u03b1 \u03ba\u03b1\u03b9 \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03b1 \u03b1\u03b9\u03c3\u03b8\u03b7\u03c4\u03ae\u03c1\u03c9\u03bd, \u03c3\u03b7\u03bc\u03b1\u03bd\u03c4\u03b9\u03ba\u03ac patterns \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c3\u03b1\u03c6\u03ad\u03c3\u03c4\u03b5\u03c1\u03b1 \u03c3\u03c4\u03b7 \u03c3\u03c5\u03c7\u03bd\u03cc\u03c4\u03b7\u03c4\u03b1 \u03ae \u03c3\u03c4\u03bf time-frequency domain \u03b1\u03c0\u03cc \u03cc,\u03c4\u03b9 \u03c3\u03c4\u03b7\u03bd \u03b1\u03c1\u03c7\u03b9\u03ba\u03ae \u03c7\u03c1\u03bf\u03bd\u03b9\u03ba\u03ae \u03ba\u03b1\u03bc\u03c0\u03cd\u03bb\u03b7.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u039c\u03c0\u03bf\u03c1\u03b5\u03af \u03b7 \u03af\u03b4\u03b9\u03b1 XAI \u03bc\u03ad\u03b8\u03bf\u03b4\u03bf\u03c2 \u03bd\u03b1 \u03b4\u03ce\u03c3\u03b5\u03b9 \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03ae \u03b5\u03be\u03ae\u03b3\u03b7\u03c3\u03b7;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u039d\u03b1\u03b9. \u03a3\u03c4\u03b7 \u03bc\u03b5\u03bb\u03ad\u03c4\u03b7, \u03bf\u03b9 Captum-based \u03ba\u03b1\u03b9 Zennit-based implementations \u03c4\u03bf\u03c5 Integrated Gradients \u03bc\u03b5 \u03af\u03b4\u03b9\u03b5\u03c2 \u03b5\u03bc\u03c6\u03b1\u03bd\u03b5\u03af\u03c2 \u03c0\u03b1\u03c1\u03b1\u03bc\u03ad\u03c4\u03c1\u03bf\u03c5\u03c2 \u03ad\u03b4\u03c9\u03c3\u03b1\u03bd \u03c3\u03c5\u03c3\u03c4\u03b7\u03bc\u03b1\u03c4\u03b9\u03ba\u03ac \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03ad\u03c2 \u03b5\u03be\u03b7\u03b3\u03ae\u03c3\u03b5\u03b9\u03c2 \u03c3\u03c4\u03bf ECG test set.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u0391\u03c1\u03ba\u03b5\u03af \u03c5\u03c8\u03b7\u03bb\u03cc accuracy \u03b3\u03b9\u03b1 \u03bd\u03b1 \u03b5\u03bc\u03c0\u03b9\u03c3\u03c4\u03b5\u03c5\u03c4\u03bf\u03cd\u03bc\u03b5 \u03c4\u03b9\u03c2 \u03b5\u03be\u03b7\u03b3\u03ae\u03c3\u03b5\u03b9\u03c2;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u038c\u03c7\u03b9. \u03a4\u03bf accuracy \u03b1\u03be\u03b9\u03bf\u03bb\u03bf\u03b3\u03b5\u03af \u03c4\u03b9\u03c2 \u03c0\u03c1\u03bf\u03b2\u03bb\u03ad\u03c8\u03b5\u03b9\u03c2, \u03cc\u03c7\u03b9 \u03b1\u03bd \u03bc\u03b9\u03b1 \u03b5\u03be\u03ae\u03b3\u03b7\u03c3\u03b7 \u03b1\u03c0\u03bf\u03b4\u03af\u03b4\u03b5\u03b9 \u03c0\u03b9\u03c3\u03c4\u03ac \u03c4\u03b7 \u03c3\u03c5\u03bc\u03c0\u03b5\u03c1\u03b9\u03c6\u03bf\u03c1\u03ac \u03c4\u03bf\u03c5 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf\u03c5, \u03c3\u03ad\u03b2\u03b5\u03c4\u03b1\u03b9 \u03c4\u03b7 \u03c7\u03c1\u03bf\u03bd\u03b9\u03ba\u03ae \u03b4\u03bf\u03bc\u03ae \u03ae \u03b1\u03bd\u03b1\u03c0\u03b1\u03c1\u03ac\u03b3\u03b5\u03c4\u03b1\u03b9 \u03bc\u03b5\u03c4\u03ac \u03b1\u03c0\u03cc software update.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a4\u03b9 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03ba\u03b1\u03c4\u03b1\u03b3\u03c1\u03ac\u03c6\u03b5\u03c4\u03b1\u03b9 \u03b3\u03b9\u03b1 XAI governance;<\/summary>\n<div class=\"td-faq-content\">\n<p>Model \u03ba\u03b1\u03b9 dataset version, framework \u03ba\u03b1\u03b9 version, backend, method, baseline, preprocessing, parameters, metric configuration, execution environment \u03ba\u03b1\u03b9 \u03b1\u03c0\u03bf\u03c4\u03b5\u03bb\u03ad\u03c3\u03bc\u03b1\u03c4\u03b1 regression tests.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a0\u03bf\u03b9\u03bf\u03c2 \u03b5\u03af\u03bd\u03b1\u03b9 \u03bf \u03b2\u03b1\u03c3\u03b9\u03ba\u03cc\u03c2 \u03c0\u03b5\u03c1\u03b9\u03bf\u03c1\u03b9\u03c3\u03bc\u03cc\u03c2 \u03c4\u03b7\u03c2 \u03b1\u03bd\u03b1\u03c3\u03ba\u03cc\u03c0\u03b7\u03c3\u03b7\u03c2;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u0397 \u03b1\u03bd\u03b1\u03b6\u03ae\u03c4\u03b7\u03c3\u03b7 \u03c0\u03b5\u03c1\u03b9\u03bf\u03c1\u03af\u03c3\u03c4\u03b7\u03ba\u03b5 \u03c3\u03c4\u03bf GitHub \u03ba\u03b1\u03b9 \u03b7 cross-framework \u03c3\u03cd\u03b3\u03ba\u03c1\u03b9\u03c3\u03b7 \u03ba\u03ac\u03bb\u03c5\u03c8\u03b5 \u03c0\u03ad\u03bd\u03c4\u03b5 explanation methods \u03ba\u03b1\u03b9 \u03ad\u03bd\u03b1 metric. \u0394\u03b5\u03af\u03c7\u03bd\u03b5\u03b9 \u03cc\u03c4\u03b9 \u03b7 \u03b1\u03c3\u03c5\u03bc\u03c6\u03c9\u03bd\u03af\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b4\u03c5\u03bd\u03b1\u03c4\u03ae, \u03cc\u03c7\u03b9 \u03c4\u03b7 \u03c3\u03c5\u03c7\u03bd\u03cc\u03c4\u03b7\u03c4\u03ac \u03c4\u03b7\u03c2 \u03c3\u03b5 \u03cc\u03bb\u03bf \u03c4\u03bf \u03c0\u03b5\u03b4\u03af\u03bf.<\/p>\n<\/div>\n<\/details>\n<\/div>\n<\/section>\n<div class=\"td-source-list\">\n<p id=\"piges\" class=\"td-source-list-title\">Sources<\/p>\n<ul>\n<li><a href=\"https:\/\/arxiv.org\/abs\/2608.21449\" target=\"_blank\" rel=\"noopener\">arXiv \u2014 Software Frameworks for Explainable AI in Time Series Classification<\/a><\/li>\n<li><a href=\"https:\/\/github.com\/fzi-forschungszentrum-informatik\/TSInterpret\" target=\"_blank\" rel=\"noopener\">GitHub \u2014 TSInterpret<\/a><\/li>\n<li><a href=\"https:\/\/github.com\/josephenguehard\/time_interpret\" target=\"_blank\" rel=\"noopener\">GitHub \u2014 time_interpret<\/a><\/li>\n<li><a href=\"https:\/\/github.com\/TimeXAIgroup\/signxai2\" target=\"_blank\" rel=\"noopener\">GitHub \u2014 SIGN-XAI-2<\/a><\/li>\n<li><a href=\"https:\/\/github.com\/understandable-machine-intelligence-lab\/Quantus\" target=\"_blank\" rel=\"noopener\">GitHub \u2014 Quantus<\/a><\/li>\n<li><a href=\"https:\/\/github.com\/JHoelli\/XTSC-Bench\" target=\"_blank\" rel=\"noopener\">GitHub \u2014 XTSC-Bench<\/a><\/li>\n<li><a href=\"https:\/\/eur-lex.europa.eu\/eli\/reg\/2024\/1689\/oj\" target=\"_blank\" rel=\"noopener\">EUR-Lex \u2014 \u039a\u03b1\u03bd\u03bf\u03bd\u03b9\u03c3\u03bc\u03cc\u03c2 (\u0395\u0395) 2024\/1689 \u03b3\u03b9\u03b1 \u03c4\u03b7\u03bd \u03c4\u03b5\u03c7\u03bd\u03b7\u03c4\u03ae \u03bd\u03bf\u03b7\u03bc\u03bf\u03c3\u03cd\u03bd\u03b7<\/a><\/li>\n<\/ul>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>\u03a4\u03bf explainable AI \u03c3\u03c4\u03b9\u03c2 \u03c7\u03c1\u03bf\u03bd\u03bf\u03c3\u03b5\u03b9\u03c1\u03ad\u03c2 \u03b1\u03bb\u03bb\u03ac\u03b6\u03b5\u03b9 \u03b1\u03bd\u03ac framework. \u0397 \u03b1\u03bd\u03b1\u03c3\u03ba\u03cc\u03c0\u03b7\u03c3\u03b7 \u03ad\u03be\u03b9 \u03b5\u03c1\u03b3\u03b1\u03bb\u03b5\u03af\u03c9\u03bd \u03b4\u03b5\u03af\u03c7\u03bd\u03b5\u03b9 \u03ba\u03b5\u03bd\u03ac \u03c3\u03b5 methods, metrics, \u03c3\u03c5\u03c7\u03bd\u03cc\u03c4\u03b7\u03c4\u03b5\u03c2 \u03ba\u03b1\u03b9 \u03b1\u03bd\u03b1\u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03b9\u03bc\u03cc\u03c4\u03b7\u03c4\u03b1.<\/p>","protected":false},"author":1,"featured_media":104945,"comment_status":"open","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_gspb_post_css":"","content-type":"","footnotes":""},"categories":[199],"tags":[9260,18400,7549,7477,18988],"class_list":["post-97888","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-techniti-noimosyni","tag-ai-governance","tag-data-science","tag-explainable-ai","tag-machine-learning","tag-chronoseires"],"blocksy_meta":{"styles_descriptor":{"styles":{"desktop":"","tablet":"","mobile":""},"google_fonts":[],"version":8}},"_links":{"self":[{"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/posts\/97888","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/comments?post=97888"}],"version-history":[{"count":1,"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/posts\/97888\/revisions"}],"predecessor-version":[{"id":104946,"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/posts\/97888\/revisions\/104946"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/media\/104945"}],"wp:attachment":[{"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/media?parent=97888"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/categories?post=97888"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/tags?post=97888"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}