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Logistic regression

model2 events
papersTODAY 04:00 UTC

Study Compares LLM-Generated Rules With Traditional Models for Heart Disease Prediction

A new arXiv paper evaluates rule-based systems produced by large language models against conventional machine learning classifiers for predicting heart disease. Using the UCI Heart Disease dataset, the authors benchmark models including logistic regression and k-nearest neighbors. The work examines whether LLM-derived decision rules can match or complement established clinical prediction methods.

research/healthcare/benchmark/llm
papersTODAY 04:00 UTC

arXiv paper proposes clustering-assisted logistic model for PU classification beyond SCAR

A new arXiv preprint examines positive-unlabeled (PU) classification when the common SCAR assumption does not hold. The authors study logistic regression approaches, including a cluster-based method and Lasso-regularized variants, and add oversampling to improve performance. The work appears as a cross-listing in cs.AI and cs.LG.

arxiv/machine-learning/classification/research