Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

Implement Logistic Regression in Python from Scratch ! In this video, we will implement Logistic Regression in Python from Scratch. We will not use any build in models, but we will understand the code ...

A complete implementation of Logistic Regression with Gradient Descent optimization from scratch using only NumPy, demonstrating mathematical foundations of binary classification for diabetes ...

1 School of Computing and Data Science, Wentworth Institute of Technology, Boston, USA. 2 Department of Computer Science and Quantitative Methods, Austin Peay State University, Clarksville, USA. 3 ...

Developed an end-to-end customer churn prediction ML pipeline using Python, pandas, and scikit-learn. Implemented and trained a logistic regression model, then deployed it as a REST API service using ...

Abstract: This paper's primary goal is to use machine learning techniques, specifically Logistic Regression and Decision Trees, to identify bogus news on social media. An innovative logistic model is ...

ABSTRACT: This paper aims to investigate the effectiveness of logistic regression and discriminant analysis in predicting diabetes in patients using a diabetes dataset. Additionally, the paper ...