Northwestern Engineering faculty and students participated in the annual forum for advances in theory, empirics, and ...

Feature selection was performed using univariate logistic regression and LASSO regression. Five machine learning algorithms—logistic regression, decision tree, multilayer perceptron, random forest, ...

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...

Our model builds upon homomorphic encryption methodologies with hardware-based security reinforcement through Software Guard Extensions (SGX), and our implementation demonstrates a practical hybrid ...

In the context of binary classification for breast cancer diagnosis, this paper offers a comparative statistical analysis of two popular classification techniques, Support Vector Machine (SVM) and ...

This article will cover the basic theory behind logistic regression, the types of logistic regression, when to use them and take you through a worked example.

Logistic regression is a statistical tool that forms much of the basis of the field of machine learning and artificial intelligence, including prediction algorithms and neural networks.

Machine learning models analyze complex patterns within medical datasets, enabling precise prediction and classification of diseases like CHD [14]- [18]. This study explores the application of three ...

Want to understand logistic regression? Explore our guide to learn its applications and advantages in data analysis.