{"id":"W4385768263","doi":"10.24963/ijcai.2023/225","title":"Optimal Decision Trees For Interpretable Clustering with Constraints","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; University of Toronto","funders":"Vector Institute; Natural Sciences and Engineering Research Council of Canada; Government of Canada; Canadian Institute for Advanced Research","keywords":"Cluster analysis; Interpretability; Constrained clustering; Computer science; Conceptual clustering; Data mining; Artificial intelligence; Machine learning; Correlation clustering; CURE data clustering algorithm","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":[0.004582367,0.001479048,0.001652263,0.001958123,0.00129317,0.001957347,0.001928454,0.002451929,0.004257683],"category_scores_gemma":[0.01948396,0.0008359458,0.001637708,0.002437864,0.00205902,0.002937367,0.001973084,0.003669152,0.0008956383],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001840836,"about_ca_system_score_gemma":0.002189772,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002813457,"about_ca_topic_score_gemma":0.005633365,"domain_scores_codex":[0.9964573,0.001771176,0.0001942317,0.0007635272,0.0006270307,0.0001867189],"domain_scores_gemma":[0.9887611,0.008749801,0.0006597916,0.0006655986,0.0009371418,0.0002264261],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001619514,0.0001047333,0.0009104363,0.0003358279,0.00008955006,0.0001521352,0.0003278635,0.805447,0.001845513,0.09645905,0.006279731,0.08788621],"study_design_scores_gemma":[0.00002351836,0.00002385899,0.0000977244,0.00003007269,0.000009885978,0.00002763057,0.00003631011,0.8883495,0.0004584389,0.1100181,0.0009154362,0.000009566169],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007492169,0.0002439481,0.9901826,0.0003332526,0.00002285232,0.00007295648,0.0002107576,0.0002594947,0.001182125],"genre_scores_gemma":[0.1978252,0.0004106444,0.7971126,0.0004356638,0.0001042407,0.0004461526,0.001728021,0.0002636359,0.001673893],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004582367,"threshold_uncertainty_score":0.02423412,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02759134347042677,"score_gpt":0.3249807839223426,"score_spread":0.2973894404519158,"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."}}