Abstract: The logistic regression model is a linear model widely used for two-category classification problems. This report examines the enhancement and improvement methods of logistic regression ...

This video is an overall package to understand L2 Regularization Neural Network and then implement it in Python from scratch. L2 Regularization neural network it a technique to overcome overfitting.

ABSTRACT: The study examined the effectiveness of financial linkages on SMEs’ access to debt finance. The study was motivated by the importance of SMEs in economic development and employment creation ...

eWeek content and product recommendations are editorially independent. We may make money when you click on links to our partners. Learn More Logistic regression is a statistical technique used to ...

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 ...

Weight decay and ℓ2 regularization are crucial in machine learning, especially in limiting network capacity and reducing irrelevant weight components. These techniques align with Occam’s razor ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end program that explains how to perform binary classification (predicting a variable with two possible discrete values) using ...

1 Departments of Computer Sciences, Nasarawa State University, Keffi, Nigeria. 2 Departments of Computer Sciences, University of Jos, Jos, Nigeria. Due to the rapid development of logistic industry, ...