Efficient semi-supervised inference for logistic regression under case-control studies

arXiv:2402.15365v1 Announce Type: cross
Abstract: Semi-supervised learning has received increasingly attention in statistics and machine learning. In semi-supervised learning settings, a labeled data set with both outcomes and covariates and an unlabeled data set with covariates only are collected. We consider an inference problem in semi-supervised settings where the outcome in the labeled data is binary and the labeled data is collected by case-control sampling. Case-control sampling is an effective sampling scheme for alleviating imbalance structure in binary data. Under …

abstract arxiv attention case control cs.lg data data set inference logistic regression machine machine learning regression semi-supervised semi-supervised learning set statistics stat.ml studies supervised learning type