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 ...

Logistic regression is an approach to supervised machine learning that models selected values to predict possible outcomes. In this course, Notre Dame professor Frederick Nwanganga provides you with a ...

Materials and methods: We compared traditional logistic regression (LR) with five ML algorithms LR with Elastic-Net, Random Forest (RF), XGBoost (XGB), Support Vector Machine, Deep Learning, and an ...

Abstract: Nowadays, heart disease is a serious medical issue, and diagnosis is crucial to providing the proper treatment to the patient. Hence, machine learning (ML)-based early diagnosis of heart ...

Joseph Berkson developed logistic regression as a general statistical model in 1944. Today, logistic regression is one of the main pillars of machine learning. From predicting Trauma and Injury ...