{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005299519,0.001495399,0.001811812,0.002840695,0.0006424948,0.001593172,0.00184046,0.0016498,0.003112516],"category_scores_gemma":[0.01047609,0.0003703961,0.001769708,0.002497209,0.0005623622,0.001759332,0.001239645,0.001595595,0.001285277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001440757,"about_ca_system_score_gemma":0.001097376,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002644612,"about_ca_topic_score_gemma":0.001829915,"domain_scores_codex":[0.9959507,0.001314744,0.0003489205,0.0005567509,0.00151272,0.0003161522],"domain_scores_gemma":[0.9934886,0.003332126,0.000457486,0.0004027187,0.00208968,0.0002294996],"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":[0.001369334,0.0006303295,0.009271241,0.0006208418,0.0003177871,0.0002593457,0.00009502169,0.1571376,0.01489072,0.003526372,0.01712646,0.794755],"study_design_scores_gemma":[0.00004538022,0.0002333744,0.001585267,0.00004413218,0.00004778648,0.0001081276,0.00002283489,0.9834651,0.00966848,0.003198425,0.001557408,0.00002369314],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05826433,0.001642024,0.9325628,0.000571882,0.0002093525,0.0005452051,0.0009265103,0.003512398,0.001765459],"genre_scores_gemma":[0.5431368,0.0004646106,0.4509706,0.0003463961,0.0001527933,0.0007581711,0.002442279,0.0002767688,0.001451718],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005299519,"threshold_uncertainty_score":0.02802688,"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."}}