{"id":"W3096829912","doi":"10.18280/ts.370403","title":"Phishing Website Detection Using Machine Learning Classifiers Optimized by Feature Selection","year":2020,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Random forest; Phishing; Feature selection; Decision tree; Computer science; Machine learning; Artificial intelligence; k-nearest neighbors algorithm; Selection (genetic algorithm); Feature (linguistics); Data mining; World Wide Web; The Internet","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":[0.001593987,0.001006786,0.00142475,0.001656916,0.000490529,0.0007323135,0.0006583479,0.001009144,0.001068277],"category_scores_gemma":[0.003033047,0.000331331,0.001083805,0.001069954,0.0001636004,0.0007803719,0.000340171,0.0009534827,0.0008507704],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005820239,"about_ca_system_score_gemma":0.0009573893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004258908,"about_ca_topic_score_gemma":0.002880095,"domain_scores_codex":[0.999019,0.0002322733,0.0001045105,0.0002430132,0.0001971545,0.0002040482],"domain_scores_gemma":[0.9985953,0.000657445,0.00009225011,0.00009664142,0.0005098523,0.00004853045],"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":[0.0009543888,0.0008847044,0.01489972,0.0001333776,0.0002476845,0.0002688476,0.0000775173,0.1621117,0.02637227,0.0005063034,0.006119543,0.7874239],"study_design_scores_gemma":[0.00003708904,0.0001822299,0.003978882,0.000009707669,0.00004995939,0.00008273779,0.00002630527,0.9865084,0.008230401,0.0004101045,0.0004693183,0.0000149343],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.427144,0.001203521,0.5616432,0.0003831657,0.000213196,0.0002841454,0.0006953285,0.006765503,0.001667846],"genre_scores_gemma":[0.8248982,0.0001654117,0.1716229,0.00009224,0.00008048039,0.0002273277,0.001438977,0.00008413987,0.001390348],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004258908,"threshold_uncertainty_score":0.008468211,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02181908028561128,"score_gpt":0.2176225694893505,"score_spread":0.1958034892037392,"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."}}