{"id":"W3199777484","doi":"10.18280/mmep.080407","title":"Accurate and Hybrid Regularization - Robust Regression Model in Handling Multicollinearity and Outlier Using 8SC for Big Data","year":2021,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universitas Sultan Ageng Tirtayasa","keywords":"Multicollinearity; Outlier; Statistics; Variance inflation factor; Regression analysis; Elastic net regularization; Regression; Lasso (programming language); Mathematics; Linear regression; Robust regression; Regression diagnostic; Mean squared error; Computer science; Econometrics; Polynomial regression","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":[],"consensus_categories":[],"category_scores_codex":[0.0002305863,0.000173677,0.0003132799,0.00007923383,0.00009378694,0.0001238055,0.00007620751,0.000105161,0.000003298864],"category_scores_gemma":[0.0002054209,0.0001586019,0.00002028836,0.0001388344,0.00002827519,0.0001362659,0.0001377383,0.0001686585,1.117982e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002260501,"about_ca_system_score_gemma":0.00002121458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009474864,"about_ca_topic_score_gemma":0.000001163186,"domain_scores_codex":[0.9989581,0.000005020894,0.0002990758,0.0004058408,0.0001028333,0.0002291479],"domain_scores_gemma":[0.9994034,0.0001565228,0.00005308682,0.0002581434,0.00004349105,0.00008532636],"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":[0.000007609593,0.00004614614,0.00004328879,0.001485128,0.00002566719,0.000002503703,0.0001637927,0.9839606,0.0137498,0.0003126402,0.000002740226,0.000200107],"study_design_scores_gemma":[0.0004315796,0.000004309498,9.431437e-7,0.000442838,0.000101133,0.00002092301,0.00004343341,0.9825459,0.01103365,0.005175905,0.00001381806,0.0001855334],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2210238,0.001143124,0.7776359,0.00003690923,0.00001478275,0.00006463492,0.00001934118,0.00003648862,0.00002504097],"genre_scores_gemma":[0.7697438,0.0003791593,0.2295173,0.000006997383,0.00006327262,0.00001251639,0.00005781882,0.0000338619,0.0001852273],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.54872,"threshold_uncertainty_score":0.6467597,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1580713876361771,"score_gpt":0.2920989461802843,"score_spread":0.1340275585441072,"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."}}