Overview Regression explains how changes in one factor influence another with clarity.Each regression type is suited for ...

Abstract: Logistic regression is a fundamental and widely used statistical method for modeling binary outcomes based on covariates. However, the presence of missing data, particularly in settings ...

3.Import the Logistic Regression model from sklearn. 4.Train the model using the training dataset. 5.Use the trained model to predict placement for new student data ...

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 ...

Objective: This study aimed to develop and validate a multivariate logistic regression model for predicting intracranial aneurysm (IA) rupture by integrating clinical data, aneurysm morphology, and ...

Background: Sepsis is a life-threatening disease associated with a high mortality rate, emphasizing the need for the exploration of novel models to predict the prognosis of this patient population.

This project aims to classify human actions based on daily activities using a custom Logistic Regression model. The model is implemented from scratch, providing a clear understanding of the underlying ...