{"id":"W2093275257","doi":"10.5430/air.v1n2p11","title":"Interpretable support vector regression","year":2012,"lang":"en","type":"article","venue":"Artificial Intelligence Research","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"European Social Fund; European Commission","keywords":"Support vector machine; Interpretability; Data mining; Fuzzy rule; Kernel (algebra); Identification (biology); Computer science; Artificial intelligence; Reduction (mathematics); Least squares support vector machine; Fuzzy logic; Kernel method; Relevance vector machine; Mathematics; Pattern recognition (psychology); Machine learning; Fuzzy set","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":[0.001447862,0.001011462,0.0009850455,0.0009101219,0.0001721702,0.001393351,0.0009930033,0.00117573,0.003280129],"category_scores_gemma":[0.006499978,0.0003680063,0.0009239423,0.0006813577,0.0004675582,0.001545741,0.0009119922,0.001653267,0.001181406],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002852706,"about_ca_system_score_gemma":0.0003830564,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005262385,"about_ca_topic_score_gemma":0.0004727357,"domain_scores_codex":[0.9986557,0.0004794733,0.00008398157,0.0001876897,0.0005335743,0.00005964825],"domain_scores_gemma":[0.9982088,0.0008778168,0.0002001771,0.0003460453,0.0003431442,0.00002403513],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001839575,0.0001375158,0.001212508,0.0004263223,0.0001579501,0.0006033428,0.0003104338,0.4877798,0.02883971,0.08413742,0.003320924,0.3928901],"study_design_scores_gemma":[0.00001043822,0.00006224153,0.0003007301,0.00002243851,0.00001578087,0.00009677832,0.00003059368,0.9723266,0.004478912,0.01931739,0.003322807,0.00001525799],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007034077,0.0002027476,0.9905748,0.0001071044,0.00004579809,0.00002327511,0.00005882992,0.0004194177,0.001534006],"genre_scores_gemma":[0.4304933,0.0009671359,0.5602641,0.0001924854,0.000198935,0.0001827878,0.0008417954,0.0002395252,0.00661992],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003280129,"threshold_uncertainty_score":0.01097316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2461539245253788,"score_gpt":0.4550938221825369,"score_spread":0.2089398976571581,"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."}}