{"id":"W2788320705","doi":"","title":"Machine learning: Supervised methods, SVM and kNN","year":2018,"lang":"fr","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre","funders":"","keywords":"Support vector machine; Machine learning; Artificial intelligence; Random forest; Logistic regression; Supervised learning; Context (archaeology); Computer science; Pattern recognition (psychology); Set (abstract data type); Artificial neural network; Biology","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":[0.003559413,0.002054053,0.002736394,0.003113482,0.0008135162,0.003577276,0.002026483,0.00336607,0.00979669],"category_scores_gemma":[0.01919553,0.0006020209,0.0008186747,0.008614444,0.002184163,0.004167997,0.002426768,0.004171569,0.007569267],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001366693,"about_ca_system_score_gemma":0.001706575,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002624068,"about_ca_topic_score_gemma":0.001919279,"domain_scores_codex":[0.9947165,0.00191184,0.0002925555,0.001182378,0.001727125,0.0001697168],"domain_scores_gemma":[0.9928282,0.003780773,0.0005743076,0.0008575179,0.00168937,0.0002698838],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001773537,0.0002108606,0.001161247,0.001691542,0.0001663818,0.00009334696,0.00013136,0.04581269,0.001969257,0.04429206,0.1093521,0.7949418],"study_design_scores_gemma":[0.0000463175,0.0001168387,0.003147934,0.0004816649,0.00006133989,0.0005042048,0.0001657704,0.6329718,0.002982949,0.2913415,0.06807971,0.00009983964],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008945595,0.05971828,0.9042778,0.007442182,0.003573317,0.0001451353,0.001197532,0.003672883,0.01102724],"genre_scores_gemma":[0.2536455,0.05723952,0.6079785,0.002742692,0.01593642,0.0009216499,0.006395099,0.002673035,0.05246751],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00979669,"threshold_uncertainty_score":0.03277314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03162811474333381,"score_gpt":0.2822962049146925,"score_spread":0.2506680901713587,"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."}}