{"id":"W2105323064","doi":"10.5539/cis.v1n2p17","title":"Research on Decision Forest Learning Algorithm","year":2008,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Overfitting; Computer science; Decision tree; Machine learning; Artificial intelligence; Tree (set theory); Root (linguistics); Tree structure; Incremental decision tree; Decision tree learning; Algorithm; Alternating decision tree; Data mining; Mathematics; Artificial neural network; Binary tree","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":[0.004904638,0.001083469,0.001630359,0.002139229,0.0008611825,0.002247888,0.001826801,0.001807119,0.00224397],"category_scores_gemma":[0.01328895,0.0005155164,0.001115037,0.004339857,0.0009633762,0.005037129,0.0008077283,0.002276755,0.001303646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009431428,"about_ca_system_score_gemma":0.001586987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002654069,"about_ca_topic_score_gemma":0.001544892,"domain_scores_codex":[0.9963998,0.001281381,0.0002454353,0.0007923361,0.001101943,0.0001791408],"domain_scores_gemma":[0.9938432,0.004208451,0.0001813538,0.0003390611,0.001335864,0.00009212431],"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":[0.0001215575,0.0001837845,0.003303252,0.0008857839,0.0001863127,0.0001442064,0.000160271,0.100292,0.001924524,0.1041718,0.006350152,0.7822763],"study_design_scores_gemma":[0.00005743546,0.0001979113,0.001396506,0.000423792,0.000118007,0.0004280949,0.0001089889,0.749575,0.004913819,0.1958207,0.04689095,0.00006881227],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0104552,0.02782419,0.9506558,0.001389732,0.0005135685,0.0001073055,0.0001360173,0.0003246426,0.008593538],"genre_scores_gemma":[0.236651,0.03646571,0.7174636,0.001175438,0.001608178,0.0002620619,0.0007588869,0.000125099,0.005490119],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004904638,"threshold_uncertainty_score":0.02593851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05377590464561675,"score_gpt":0.3408806680468781,"score_spread":0.2871047634012613,"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."}}