Learn how to implement the K-Nearest Neighbors (KNN) algorithm from scratch in Python! This tutorial covers the theory, ...

A robust, from-scratch implementation of the CART (Classification and Regression Trees) algorithm for classification tasks, developed as part of the DATA2060 Machine Learning course. ├── data/ # Train ...

Abstract: The K-Nearest Neighbors (kNN) algorithm, a cornerstone of supervised learning, relies on similarity measures constrained by real-number-based distance metrics. A critical limitation of ...

Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to ...

ABSTRACT: The 2018 General Education Program in Vietnam emphasizes personalized learning and the application of technology in teaching. This study proposes a customized learning system integrating ...

The emergence of using Machine Learning Techniques in software testing started in the 2000s with the rise of Model-Based Testing and early bug prediction models trained on historical defect data. It ...

Abstract: This study proposed an effective machine learning (ML)-based fault diagnosis method for demagnetization faults, including “healthy, 30% unipolar demagnetization, 50% multimagnet ...

The year 2024 is the time when most manual things are being automated with the assistance of Machine Learning algorithms. You’d be surprised at the growing number of ML algorithms that help play chess ...

1 The Graduate School, ICAR-Indian Agricultural Research Institute, New Delhi, India 2 ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India Early prediction of pest occurrences can ...