{"id":"W4381137345","doi":"10.22214/ijraset.2023.54035","title":"Decision Tree Learning Based Feature Selection and Evaluation for Image Classification","year":2023,"lang":"en","type":"article","venue":"International Journal for Research in Applied Science and Engineering Technology","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institute for Advanced Research","keywords":"Artificial intelligence; Decision tree; Computer science; Classifier (UML); Machine learning; Decision tree learning; Pattern recognition (psychology); Incremental decision tree; ID3 algorithm; Feature selection; Logistic model tree; Contextual image classification; Data mining; Image (mathematics)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007732146,0.00007021482,0.000075282,0.002580734,0.0003890982,0.0004370706,0.0006575136,0.00008676818,6.028007e-7],"category_scores_gemma":[0.002469088,0.00006654114,0.00001356732,0.001806728,0.0001081179,0.0003528013,0.0001416218,0.0004597436,0.000002381712],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002375769,"about_ca_system_score_gemma":0.0001902574,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001934154,"about_ca_topic_score_gemma":0.000004801399,"domain_scores_codex":[0.9983849,0.00002236385,0.000158505,0.0003538917,0.0007758652,0.0003044755],"domain_scores_gemma":[0.9985208,0.0004209782,0.00005863771,0.0001185446,0.0008200994,0.00006092352],"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":[0.00003870105,0.00001572094,0.0003821954,0.00001431529,0.000004853065,0.000001383639,0.00006624985,0.008480374,0.1462382,0.07372014,0.0003982074,0.7706397],"study_design_scores_gemma":[0.0005437312,0.00007773428,0.005968832,0.00003110515,0.000001277774,0.00002658188,0.00007826488,0.9679361,0.001306351,0.01578027,0.00818437,0.00006536136],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08600093,0.00004327714,0.8979024,0.01490339,0.0003647501,0.0004849365,0.000002008128,0.0001941683,0.0001041177],"genre_scores_gemma":[0.9163179,0.00006136102,0.08329748,0.00001155035,0.00006249941,0.0002143669,0.00001083072,0.000006853172,0.00001714992],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9594557,"threshold_uncertainty_score":0.4214682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07829141481452324,"score_gpt":0.4331141711061334,"score_spread":0.3548227562916102,"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."}}