{"id":"W3172756271","doi":"","title":"Comparison of Traditional Linear SVM Implementation Against MapReduce SVM Implementation","year":2014,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Advanced Computational Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Support vector machine; Computer science; Data mining; Artificial intelligence; Machine learning","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":[0.0004814643,0.0006210518,0.0005384979,0.0007148747,0.0005603061,0.001081546,0.002072892,0.0005441899,0.01476838],"category_scores_gemma":[0.002668605,0.0003241378,0.0003796412,0.001309769,0.0001997436,0.00171952,0.0005058863,0.0008608888,0.006231841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005933048,"about_ca_system_score_gemma":0.001653756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01280536,"about_ca_topic_score_gemma":0.01486781,"domain_scores_codex":[0.9991667,0.0001048168,0.00006190207,0.000158442,0.0003316963,0.0001763419],"domain_scores_gemma":[0.9984603,0.0002741769,0.00004151949,0.0002866842,0.0008214146,0.0001159779],"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":[0.004857514,0.001833995,0.006806459,0.001045138,0.0004069546,0.0003885014,0.0002012929,0.04886077,0.03505588,0.004800007,0.1257616,0.769982],"study_design_scores_gemma":[0.001114334,0.001560039,0.01698546,0.00009846419,0.0002570578,0.0006029918,0.0009769463,0.8314941,0.08670788,0.005534023,0.05455773,0.0001109462],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6422231,0.004579933,0.2048288,0.001841579,0.003005475,0.0005209564,0.005418395,0.07155368,0.06602821],"genre_scores_gemma":[0.7765914,0.001126238,0.1798175,0.0005189626,0.0001912289,0.000230491,0.01024395,0.001845529,0.02943462],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01476838,"threshold_uncertainty_score":0.04940522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03997575690565854,"score_gpt":0.3439182341690793,"score_spread":0.3039424772634208,"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."}}