{"id":"W4399895491","doi":"10.18280/ria.380306","title":"The Impact of Oversampling and Undersampling on Aspect-Based Sentiment Analysis of Indramayu Tourism Using Logistic Regression","year":2024,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Data Mining and Machine Learning Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Undersampling; Logistic regression; Oversampling; Tourism; Statistics; Econometrics; Mathematics; Computer science; Artificial intelligence; Geography","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":[0.004688066,0.000936941,0.0007944616,0.0008950292,0.0006668246,0.0008846287,0.0005712585,0.0004768023,0.000432277],"category_scores_gemma":[0.01148122,0.0002131148,0.001020815,0.0008405232,0.0005309656,0.00105038,0.0008961389,0.000920643,0.0003662193],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004216229,"about_ca_system_score_gemma":0.0005616195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005721375,"about_ca_topic_score_gemma":0.006663292,"domain_scores_codex":[0.9981331,0.0008124032,0.0001817923,0.0003524795,0.0003744637,0.0001457305],"domain_scores_gemma":[0.9955879,0.002529684,0.0004675213,0.0004535773,0.0008627247,0.00009853702],"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":[0.002190565,0.0006164822,0.1795384,0.0006593087,0.0005008687,0.001166737,0.002128692,0.1810126,0.05093503,0.001982756,0.006603221,0.5726653],"study_design_scores_gemma":[0.0000387363,0.0003583239,0.05060969,0.00008553542,0.0001214548,0.0003348767,0.00107187,0.925006,0.01780004,0.001549507,0.002969589,0.00005453783],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8615766,0.001390621,0.1331778,0.0005622365,0.0002337413,0.0001783351,0.0004739534,0.0006869824,0.001719737],"genre_scores_gemma":[0.9564461,0.000301253,0.04106619,0.0001125538,0.00006175885,0.00009491521,0.001217523,0.0000540037,0.0006456373],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005721375,"threshold_uncertainty_score":0.02479315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0827132864789696,"score_gpt":0.3777684491502201,"score_spread":0.2950551626712505,"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."}}