{"id":"W7026791661","doi":"","title":"AN ARGMAX ONE-VS-ALL APPROACH FOR MULTI-CLASS ANOMALY-BASED NETWORK INTRUSION DETECTION SYSTEM","year":2022,"lang":"en","type":"other","venue":"Covenant University Repository (Covenant University)","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Feature selection; Intrusion detection system; The Internet; Ensemble learning; Random forest; Boosting (machine learning); Multilayer perceptron; Network security; Process (computing)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003776906,0.0005190531,0.0005743302,0.0006452767,0.0007742866,0.00006808009,0.001216995,0.000951086,0.00004757827],"category_scores_gemma":[0.00003215737,0.0005720226,0.0004419582,0.0004548599,0.0003196785,0.00002269393,0.0005863292,0.0004343172,0.000008965778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007372719,"about_ca_system_score_gemma":0.0006453022,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003371375,"about_ca_topic_score_gemma":0.0001963195,"domain_scores_codex":[0.996882,0.0004040139,0.0003113905,0.001055453,0.0005294028,0.000817744],"domain_scores_gemma":[0.9977178,0.00003205567,0.0005325156,0.001029214,0.0001975286,0.0004908801],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.02568213,0.009713167,0.006448444,0.01475408,0.007268621,0.002840893,0.0007664434,0.02079604,0.5623387,0.002414685,0.331627,0.01534982],"study_design_scores_gemma":[0.00295951,0.001582356,0.000102194,0.0001440149,0.0003525128,0.00002426101,0.001067001,0.02132793,0.006029256,8.98338e-7,0.9655792,0.0008309358],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.01527696,0.0009911252,0.7029611,0.0001137317,0.003974225,0.006864968,0.002374737,0.0009731626,0.26647],"genre_scores_gemma":[0.1707096,0.001277321,0.0311418,0.0002981208,0.002595279,0.00001450047,0.007835423,0.0008324695,0.7852955],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.6718193,"threshold_uncertainty_score":0.9996731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01987634235474003,"score_gpt":0.2188743985998101,"score_spread":0.1989980562450701,"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."}}