{"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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001288534,0.00007383148,0.00007234338,0.000524651,0.001455678,0.00059339,0.0009705594,0.00002641059,0.000002396138],"category_scores_gemma":[0.00005633367,0.00006154068,0.00001497048,0.001679263,0.0003733609,0.007385445,0.0006222503,0.0002165797,0.0002578367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003382004,"about_ca_system_score_gemma":0.0001242308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009965557,"about_ca_topic_score_gemma":1.801874e-7,"domain_scores_codex":[0.9984671,0.00002290257,0.0002047842,0.000249097,0.0007749864,0.0002811552],"domain_scores_gemma":[0.9988793,0.0001881491,0.00005181797,0.0003828154,0.0003533818,0.0001445399],"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":[7.173431e-7,0.0000108323,0.0001138782,0.000001302781,4.950151e-7,9.328213e-7,0.0007802389,0.0005600849,0.000003526891,0.04457377,0.001673783,0.9522805],"study_design_scores_gemma":[0.0001489978,0.0001328976,0.02506377,0.00001544242,2.008492e-7,0.00005519053,0.00003898226,0.9133216,0.00007608566,0.0005634628,0.06049958,0.00008382869],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02011403,0.000008950567,0.9752967,0.0002059023,0.0001812245,0.00008976294,0.000001832713,0.00009396532,0.004007606],"genre_scores_gemma":[0.3321827,0.0001175321,0.6670079,0.0005298311,0.00008802383,0.00001682047,0.000007581739,0.00000256396,0.00004711332],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9521966,"threshold_uncertainty_score":0.9998443,"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."}}