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 ...

Lorepy offers distinct advantages over traditional methods like stacked bar plots. By employing a linear model, Lorepy captures overall trends across the entire feature range. It avoids arbitrary ...

Abstract: —The objective is to more accurately forecast phishing attacks that harvest sensitive data from unsuspecting users by utilizing Logistic Regression in comparison to the Novel Random Forest ...

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 ...

Abstract: This study combined linear discriminant analysis (LDA) and multivariate logistic regression models to systematically analyze key indicators in flood prediction, aiming to identify factors ...

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 recent years, a learning method for classifiers using tensor networks (TNs) has attracted attention. When constructing a classification function for high-dimensional data using a basis function ...

ABSTRACT: Road traffic accidents are one of the global safety and socioeconomic challenges. According to WHO (2024), it has caused over 1.19 million annual fatalities. It is also projected to cause ...