{"id":"W4401164141","doi":"10.1109/bmsb62888.2024.10608236","title":"Automated Hyperparameter Tuning and Ensemble Machine Learning Approach for Network Traffic Classification","year":2024,"lang":"en","type":"article","venue":"","topic":"Internet Traffic Analysis and Secure E-voting","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Humber Polytechnic; Toronto Metropolitan University","funders":"","keywords":"Hyperparameter; Computer science; Machine learning; Artificial intelligence; Ensemble learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002786811,0.0008476255,0.001242558,0.001356075,0.0005990512,0.0008583884,0.001192673,0.001128721,0.0008109095],"category_scores_gemma":[0.006247035,0.0003296822,0.0006878325,0.0009875275,0.0003736951,0.001339713,0.0007430855,0.001505503,0.0002682165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006866951,"about_ca_system_score_gemma":0.0008326069,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002622886,"about_ca_topic_score_gemma":0.003651227,"domain_scores_codex":[0.9986227,0.0006413411,0.00008636886,0.0002408734,0.0002838591,0.0001249308],"domain_scores_gemma":[0.997146,0.001407068,0.00020646,0.0004594326,0.0007084034,0.00007261969],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007945747,0.0001120595,0.002772347,0.00002253705,0.00008788885,0.00003716862,0.00005716441,0.7973889,0.002754667,0.002965924,0.001078411,0.1926434],"study_design_scores_gemma":[0.000001528502,0.00000834683,0.0001183682,0.00000132446,0.000003641998,0.000004876601,0.000002836515,0.9985093,0.0003916296,0.0008659963,0.00008973201,0.00000237859],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04895308,0.0002074016,0.9490587,0.0001153624,0.00003520687,0.00003948236,0.00004281276,0.0007020904,0.0008458495],"genre_scores_gemma":[0.7757152,0.0001330075,0.2223465,0.0001055601,0.00008774141,0.0001357523,0.0002611742,0.00009411942,0.001120755],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002786811,"threshold_uncertainty_score":0.01473826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0263204799489028,"score_gpt":0.2539122902240004,"score_spread":0.2275918102750976,"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."}}