{"id":"W2115572918","doi":"10.1109/nafips.2003.1226753","title":"An information theoretic approach to generating membership functions from real data","year":2004,"lang":"en","type":"article","venue":"","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Fuzzy classification; Defuzzification; Fuzzy set operations; Fuzzy logic; Membership function; Fuzzy number; Data mining; Fuzzy set; Type-2 fuzzy sets and systems; Neuro-fuzzy; Mathematics; Entropy (arrow of time); Computer science; Mathematical optimization; Artificial intelligence; Fuzzy control system","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":[0.007205536,0.001210546,0.001275717,0.002825766,0.0006993028,0.002242553,0.002273869,0.001583288,0.002223874],"category_scores_gemma":[0.02188035,0.0006504485,0.001504298,0.001682565,0.002943114,0.004299094,0.001884053,0.00250064,0.0005779868],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001119825,"about_ca_system_score_gemma":0.0009430076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007160232,"about_ca_topic_score_gemma":0.0006063701,"domain_scores_codex":[0.9963605,0.001569019,0.0002498463,0.0004870744,0.00124518,0.00008839233],"domain_scores_gemma":[0.9907688,0.0067007,0.0005271353,0.001092145,0.0008258654,0.000085336],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001040023,0.0001172804,0.0005459184,0.0005817529,0.0001872529,0.0002190646,0.0004508876,0.3991409,0.005475736,0.428836,0.001450118,0.162891],"study_design_scores_gemma":[0.00002288389,0.0001143271,0.0001988742,0.0001294674,0.00003790996,0.0002003162,0.00007364831,0.6816367,0.004508119,0.3069481,0.006060818,0.00006893019],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0009128784,0.0001251842,0.9982046,0.0001062425,0.00002141056,0.00002246199,0.00002233365,0.00004077193,0.000544104],"genre_scores_gemma":[0.1442237,0.0006390857,0.853125,0.0002098646,0.0001912414,0.000382133,0.0002001265,0.00006430206,0.0009644836],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007205536,"threshold_uncertainty_score":0.03810692,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03835122567791527,"score_gpt":0.2384260671297555,"score_spread":0.2000748414518403,"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."}}