{"id":"W4385078096","doi":"10.18280/isi.280305","title":"Optimization of Hyperparameters in Machine Learning for Enhancing Predictions of Student Academic Performance","year":2023,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universitas Diponegoro","keywords":"Hyperparameter; Machine learning; Artificial intelligence; Computer science","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":[0.008838724,0.001536036,0.001009222,0.0011446,0.0004000638,0.001428729,0.0009179058,0.001625515,0.000660247],"category_scores_gemma":[0.02642637,0.0005335201,0.0006580643,0.0009402955,0.0008353143,0.001422377,0.001044934,0.002076754,0.000597007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006464897,"about_ca_system_score_gemma":0.001353717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002113285,"about_ca_topic_score_gemma":0.00169317,"domain_scores_codex":[0.9965081,0.002448879,0.0001568181,0.0003976791,0.0003367056,0.0001518786],"domain_scores_gemma":[0.9904847,0.007246623,0.0007421312,0.0007430916,0.0006768114,0.0001067334],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000220074,0.0002593258,0.01020649,0.0001704228,0.0001746464,0.00005695916,0.0001609213,0.857725,0.005825622,0.002476194,0.001104132,0.1216201],"study_design_scores_gemma":[0.00004278764,0.0001535947,0.003695358,0.00008778115,0.00005921787,0.00003758715,0.00004632447,0.9848121,0.00543077,0.00479665,0.0008052022,0.00003263137],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1606229,0.002323619,0.8317015,0.0005660597,0.00008384739,0.0002876472,0.0001635071,0.001778419,0.002472627],"genre_scores_gemma":[0.8789558,0.0005195414,0.1189458,0.0001613194,0.00004443774,0.000359834,0.000284355,0.0001497828,0.0005789899],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008838724,"threshold_uncertainty_score":0.04674423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01902726775748292,"score_gpt":0.2746351486327378,"score_spread":0.2556078808752549,"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."}}