IEEE

Fuzzy LASSO Logistic Regression: A Regularized Framework for Interpretable Binary Classification Under Uncertainty

Abstract: Fuzzy classification models are important for handling uncertainty and heterogeneity in high-dimensional data. Although recent fuzzy logistic regression approaches have demonstrated ...
Hosted on MSN

Build logistic regression in Python from scratch easily

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 ...
Frontiers

A machine learning-based predictive nomogram for early neurological improvement after thrombolysis in acute ischemic stroke

Background: Early neurological improvement (ENI) is a critical prognostic indicator for acute ischemic stroke (AIS) patients undergoing intravenous thrombolysis with recombinant tissue plasminogen ...
GitHub

This is a beginner data analytics project with model building.

There was an error while loading. Please reload this page. This project applies Logistic Regression to predict whether a passenger aboard the Titanic survived. It ...
IEEE

Comparative Analysis of Sparse Multinomial Logistic Regression and Convolutional Neural Networks for Multi-Class Image Classification

Abstract: The classification problem represents a funda-mental challenge in machine learning, with logistic regression serving as a traditional yet widely utilized method across various scientific ...
Frontiers

CT-based radiomics predicts HRD score and HRD status in patients with ovarian cancer

Introduction: This study predicted HRD score and status based on intra- and peritumoral radiomics in patients with ovarian cancer (OC) for better guiding the use of PARPi in clinical. Methods: A total ...