{"id":"W7018179623","doi":"","title":"A Comparative Evaluation of Machine Learning Models and EDA through Tableau Using CICIDS2017 Dataset","year":2023,"lang":"en","type":"other","venue":"NORMA","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Random forest; Linear discriminant analysis; Python (programming language); AdaBoost; Decision tree; Artificial neural network; Statistical classification; Supervised learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005369573,0.002849929,0.001782001,0.008623241,0.001292414,0.003988039,0.002346651,0.001603669,0.005040931],"category_scores_gemma":[0.01257259,0.0003355175,0.002157389,0.006258632,0.0006917594,0.003633483,0.001091081,0.001404192,0.002970695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004201579,"about_ca_system_score_gemma":0.002224799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06389345,"about_ca_topic_score_gemma":0.06280541,"domain_scores_codex":[0.9955121,0.001127143,0.0004823091,0.001056751,0.001516106,0.0003056157],"domain_scores_gemma":[0.9933614,0.00365792,0.0002859681,0.0008132634,0.001677497,0.0002039571],"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":[0.00218225,0.001804741,0.02949561,0.002902696,0.00100405,0.0004171054,0.0002607984,0.1577754,0.002134624,0.007214117,0.2632507,0.5315579],"study_design_scores_gemma":[0.0001761939,0.0007111507,0.01503958,0.0003757849,0.0002194335,0.00031678,0.0006952622,0.915442,0.005979302,0.004697531,0.05620953,0.0001374476],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4901822,0.04866583,0.08993235,0.006286429,0.00490407,0.001533281,0.2438649,0.05102251,0.06360844],"genre_scores_gemma":[0.4489509,0.006168181,0.1529615,0.0007031055,0.0003417285,0.0007080577,0.375885,0.0009122329,0.01336938],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06389345,"threshold_uncertainty_score":0.1270431,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1688295358803433,"score_gpt":0.3576173925098603,"score_spread":0.188787856629517,"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."}}