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 ...

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 ...

We developed machine learning (ML) algorithms and investigated their performance in predicting patients’ current CVD risk (coronary heart disease and stroke in this study). Materials and methods: We ...

For machine learning approach, we analyzed XGBoost tree based classifier to obtain high scored classification. Using the generalized linear model for logistic regression makes it possible to analyze ...

In this paper, we examine the various machine learning models for detecting heart diseases early and propose a method of optimized logistic regression (OLR) to make predictions more accurate. The ...