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.

This set of notebooks enables the analysis of comorbidities associated with male infertility using structured EHR data. First, we identified nonoverlapping patients with male infertility and patients ...

Low-dose CT imaging is designed to reduce the radiation dose to the patient by reducing the intensity of the X-rays to obtain CT images [1]. However, this dose reduction can significantly increase the ...

In Computed Tomography (CT), the beam hardening artifacts are caused by polychromatic X-ray beams applied in real medical imaging. In this article, we applied the recently proposed box-constrained ...

Issue: #43 - Added Logistic Regression interface with binary and multiclass support - Added support for GD and Newton optimization methods - Added L2 regularization support - Added comprehensive test ...