{"id":"W4403534926","doi":"10.1109/codit62066.2024.10708595","title":"Confusion Matrix Explainability to Improve Model Performance: Application to Network Intrusion Detection","year":2024,"lang":"en","type":"article","venue":"","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Intrusion detection system; Confusion; Computer science; Confusion matrix; Matrix (chemical analysis); Intrusion; Computer security; Artificial intelligence; Materials science; Geology; Psychology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003859445,0.0001379288,0.0001067167,0.000143713,0.0002911503,0.000201071,0.0004085801,0.00008984888,0.00001413905],"category_scores_gemma":[0.000009211615,0.0001236215,0.00005549827,0.001112433,0.00001183931,0.0003747995,0.0003635196,0.0001382279,0.0003065126],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001810542,"about_ca_system_score_gemma":0.00004778045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004806047,"about_ca_topic_score_gemma":0.00001786242,"domain_scores_codex":[0.9986508,0.00001699613,0.000262518,0.0006270955,0.0001914525,0.0002511284],"domain_scores_gemma":[0.9990191,0.00002662904,0.00003001646,0.0006556669,0.0001103996,0.0001581271],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001225835,0.00002434647,0.00001865835,0.00003359517,0.000002881654,2.051195e-7,0.000187936,0.02644443,0.08561542,0.0466008,0.001513657,0.8395458],"study_design_scores_gemma":[0.00002961432,0.0001501975,0.0001896787,0.00001311786,0.000003195909,0.00000399276,0.000008971371,0.9191994,0.05154622,0.006076964,0.02262036,0.0001582901],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06198911,0.00001524725,0.9329425,0.001438132,0.0001964295,0.000996901,0.000001928227,0.001409209,0.001010617],"genre_scores_gemma":[0.8821018,0.00001266191,0.115465,0.0004161716,0.000145791,0.000874221,0.000002117917,0.00001182794,0.0009704257],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.892755,"threshold_uncertainty_score":0.5041139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006296345916826864,"score_gpt":0.26212436347482,"score_spread":0.2558280175579931,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}