{"id":"W2908387075","doi":"10.1109/icebe.2018.00014","title":"Meta-Feature Based Data Mining Service Selection and Recommendation Using Machine Learning Models","year":2018,"lang":"en","type":"article","venue":"","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Support vector machine; Machine learning; Artificial intelligence; Feature selection; Data mining; Quality of service; Meta learning (computer science); Multilayer perceptron; Web service; Process (computing); Service (business); Perceptron; Selection (genetic algorithm); Artificial neural network; World Wide Web; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004526447,0.0001049738,0.0001187607,0.0000736261,0.0003720466,0.0002587759,0.0004908647,0.00004342337,0.00004877236],"category_scores_gemma":[0.00001674815,0.00008963704,0.00001352001,0.000519259,0.00001281117,0.001460846,0.0004252637,0.0001117699,0.000005978666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001480901,"about_ca_system_score_gemma":0.0000372221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004938625,"about_ca_topic_score_gemma":0.0003395634,"domain_scores_codex":[0.9991044,0.00005616865,0.0001212386,0.0004721365,0.000101425,0.0001446343],"domain_scores_gemma":[0.9992307,0.00006497931,0.00008196977,0.0004527752,0.0001156535,0.00005392091],"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":[0.00002405966,0.0002417008,0.001011177,0.00008546282,0.0009632388,0.000001989291,0.002284305,0.01132251,0.01173288,0.01247967,0.008557971,0.951295],"study_design_scores_gemma":[0.0001136622,0.00002644196,0.00002292101,0.000004952554,0.00009543751,0.00001154938,0.00001952606,0.9888077,0.0004986639,0.0001612453,0.01012889,0.0001089923],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002415423,0.00003451003,0.9941031,0.002708271,0.00005028032,0.00007393256,0.00002660237,0.0001694179,0.0004184609],"genre_scores_gemma":[0.04444621,0.00000474223,0.9542103,0.0008337803,0.00007894389,0.000006424401,0.0002860308,0.000009056749,0.0001244807],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9774852,"threshold_uncertainty_score":0.3655292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2351521537479223,"score_gpt":0.3235037021648072,"score_spread":0.08835154841688489,"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."}}