Regularized logistic regression without a penalty term: An application to cancer classification with microarray data

► EDAs can be used to find regularized logistic classifiers. It avoids the determination of the regularization term. ► EDA is not influenced by large number of covariates. ► Yields to significant better performance on AUC measure, compared to ridge and Lasso logistic regressions.