{"id":"W2098970170","doi":"10.1109/aiccsa.2008.4493598","title":"Privacy preserving ID3 using Gini Index over horizontally partitioned data","year":2008,"lang":"en","type":"article","venue":"","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; ID3; Entropy (arrow of time); Decision tree; Overhead (engineering); Computation; Index (typography); ID3 algorithm; Data mining; Protocol (science); Private information retrieval; Tree (set theory); Secure multi-party computation; Decision tree learning; Algorithm; Incremental decision tree; Computer security; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.008473621,0.0006301299,0.001569821,0.001628906,0.001848885,0.00326041,0.001931363,0.0010084,0.001481611],"category_scores_gemma":[0.01879896,0.0004171402,0.001371626,0.003027007,0.00200421,0.004726142,0.00472986,0.002484383,0.0005510687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002630027,"about_ca_system_score_gemma":0.00411764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001712164,"about_ca_topic_score_gemma":0.001308288,"domain_scores_codex":[0.9906398,0.003292156,0.0007345206,0.00138956,0.003300906,0.0006429438],"domain_scores_gemma":[0.9885148,0.004027294,0.001063251,0.004998239,0.001070846,0.0003256011],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001183579,0.0002129265,0.00711566,0.0002443809,0.0002694611,0.0004951379,0.001244231,0.1799375,0.0206753,0.4726163,0.007144699,0.3088608],"study_design_scores_gemma":[0.00007935935,0.0001362808,0.00107613,0.00003356721,0.00005743712,0.0004252435,0.0001497616,0.6476666,0.03256564,0.3085332,0.009206373,0.00007036859],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02431998,0.0001810343,0.9715646,0.0004091063,0.00003889782,0.0001887579,0.0003696752,0.0006452543,0.002282748],"genre_scores_gemma":[0.4796655,0.0002608181,0.5154796,0.0002122462,0.00006588588,0.0004434349,0.00121367,0.000226221,0.002432578],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008473621,"threshold_uncertainty_score":0.04481333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1220442265914212,"score_gpt":0.3183589478611433,"score_spread":0.1963147212697221,"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."}}