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Cai Cai's Machine Learning Sklearn Class: Understandable from Scratch, from Model Invocation to Practical Implementation

The design of sklearn follows the "Swiss Army Knife" principle, integrating six core modules: Data Preprocessing: Similar to ...
SciELO

Obesity classification: a comparative study of machine learning models excluding weight and height data

OBJECTIVE: Obesity is a global health problem. The aim is to analyze the effectiveness of machine learning models in predicting obesity classes and to determine which model performs best in obesity ...
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 ...
Hosted on MSN

Build Logistic Regression From Scratch In Python – You Won'T Believe How Easy It Is!

Learn how to implement Logistic Regression from scratch in Python with this simple, easy-to-follow guide! Perfect for beginners, this tutorial covers every step of the process and helps you understand ...
Frontiers

Expectation-maximization alternating least squares for tensor network logistic regression

1 Department of Computer Science, Nagoya Institute of Technology, Aichi, Japan 2 RIKEN Center for Advanced Intelligence Project, Tokyo, Japan In recent years, a learning method for classifiers using ...
GitHub

README.md

Overview This project demonstrates a Logistic Regression classification model applied to a dataset for predicting the target variable based on features. The dataset is processed and analyzed using ...