Implement Logistic Regression in Python from Scratch ! In this video, we will implement Logistic Regression in Python from ...

Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...

Abstract: Data island effectively blocks the practical application of machine learning. To meet this challenge, a new framework known as federated learning was created. It allows model training on a ...

In forecasting economic time series, statistical models often need to be complemented with a process to impose various constraints in a smooth manner. Systematically imposing constraints and retaining ...

Age regression therapy involves acting younger than you are, whether that is only a few years younger than your current age or returning to a child-like or infant-like state. Age regression therapy ...

ABSTRACT: Introduction: Biopsy procedures represent an essential diagnostic tool in the management of oral lesions. This study aims to evaluate the knowledge, attitudes, and practices of dental ...

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 ...

The output variable must be either continuous nature or real value. The output variable has to be a discrete value. The regression algorithm’s task is mapping input value (x) with continuous output ...