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The rapid uptake of supervised machine learning (ML) in clinical prediction modelling, particularly for binary outcomes based on tabular data, has sparked debate about its comparative advantage over ...

Abstract: The logistic regression model is a linear model widely used for two-category classification problems. This report examines the enhancement and improvement methods of logistic regression ...

This set of notebooks enables the analysis of comorbidities associated with male infertility using structured EHR data. First, we identified nonoverlapping patients with male infertility and patients ...

Department of Mathematics, Statistics and Actuarial Science, Faculty of Health, Natural Resources and Applied Sciences, Namibia University of Science and Technology, Windhoek, Namibia. Food insecurity ...

Learn how to implement Logistic Regression from scratch in Python with this simple, easy-to-follow guide! Perfect for beginners, this tutorial covers every step of the process and helps you understand ...

In Table 3, the VIF values for each variable are < 5, which has been reduced as multicollinearity between variables. 3.3. Use the Entropy Weight Method to Weight the Data When exploring the factors ...

This repository contains an analysis of the Kaggle Machine Learning & Data Science Survey dataset, focusing on salary prediction using ordinal logistic regression and other classification models.