{"id":"W2232470570","doi":"10.5539/mas.v9n13p188","title":"Providing a Combination Classification (Honeybee Clooney and Decision Tree) Based on Developmental Learning","year":2015,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Imbalanced Data Classification Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Decision tree; Classifier (UML); Ensemble learning; MATLAB; Machine learning; Artificial intelligence; Decision tree learning; Data mining; Pattern recognition (psychology)","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":[0.001495783,0.0005610045,0.0006569448,0.001541138,0.0005276584,0.001210478,0.001099221,0.0007299988,0.001743498],"category_scores_gemma":[0.003783512,0.0002175009,0.0006343891,0.001149344,0.0002541319,0.001625268,0.0008094769,0.0006727486,0.0006228046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006957816,"about_ca_system_score_gemma":0.0007744882,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002100645,"about_ca_topic_score_gemma":0.00301644,"domain_scores_codex":[0.998297,0.0002942079,0.0001334743,0.0003994673,0.000777939,0.00009780026],"domain_scores_gemma":[0.9981623,0.000471791,0.0001601653,0.0002098759,0.000902398,0.00009345752],"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":[0.0002861092,0.0002315894,0.0162639,0.0001837172,0.0001659604,0.0001473972,0.0002065391,0.03413865,0.01988519,0.004716618,0.005794783,0.9179795],"study_design_scores_gemma":[0.00004582551,0.0003115891,0.01234367,0.00005550569,0.0001253233,0.0004700899,0.0002102976,0.9461064,0.02531135,0.005284675,0.009677005,0.00005824896],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07966539,0.000475833,0.9129367,0.0004425601,0.0001830271,0.0002461851,0.0002178809,0.001374359,0.004458069],"genre_scores_gemma":[0.5492154,0.000323665,0.4433873,0.0002461249,0.00009508422,0.0003148921,0.0006870247,0.00009750028,0.005632974],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002100645,"threshold_uncertainty_score":0.00791055,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04718113927339433,"score_gpt":0.2728182754613657,"score_spread":0.2256371361879714,"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."}}