{"id":"W4312096853","doi":"10.18280/ria.360511","title":"Stabbing of Intrusion with Learning Framework Using Auto Encoder Based Intellectual Enhanced Linear Support Vector Machine for Feature Dimensionality Reduction","year":2022,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Intrusion detection system; Artificial intelligence; Dimensionality reduction; Machine learning; Support vector machine; Curse of dimensionality; Data mining; Pattern recognition (psychology)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004746624,0.0004638797,0.0004971258,0.0004607576,0.0002589863,0.0005161234,0.0006881786,0.000409451,0.0009436634],"category_scores_gemma":[0.001035037,0.000203656,0.0005605762,0.0003772437,0.0003095173,0.0009100023,0.0005447922,0.0008300157,0.0003545098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003670205,"about_ca_system_score_gemma":0.0006965532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003712673,"about_ca_topic_score_gemma":0.003110232,"domain_scores_codex":[0.9996275,0.00006434106,0.0000328684,0.00009761953,0.0001380255,0.0000396167],"domain_scores_gemma":[0.999685,0.00009781583,0.00003831919,0.00004827503,0.0001166853,0.00001384541],"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":[0.0001900727,0.0002128208,0.002359877,0.0001141561,0.0001096366,0.0002060278,0.000188049,0.2239839,0.03399299,0.009365053,0.002604397,0.7266729],"study_design_scores_gemma":[0.000004193766,0.00007037877,0.0003190312,0.000004140921,0.00001161234,0.00004875785,0.000006709267,0.9917912,0.005868982,0.001190159,0.0006773545,0.000007444891],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03247341,0.0003224549,0.9639593,0.0001077538,0.00004335219,0.00004540645,0.00004897851,0.002080156,0.0009192164],"genre_scores_gemma":[0.7061325,0.0003521314,0.289387,0.0001250827,0.0000451642,0.0001835702,0.0003375693,0.00007456836,0.003362342],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003712673,"threshold_uncertainty_score":0.007382154,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02978872790352747,"score_gpt":0.2721733312923236,"score_spread":0.2423846033887961,"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."}}