Abstract: Because of their transparency, interpretability, and efficiency in classification tasks, decision tree algorithms are the foundation of many Business Intelligence (BI) and Analytics ...

ML powered system that predicts most suitable crop using ensemble(hard voting) of Decision Tree, Random Forest, and Gradient Boosting models implemented from scratch ...

From the perspective of student consumption behavior, a data-driven framework for screening student loan eligibility was developed using K-means clustering analysis and decision tree models. A ...

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: From the perspective of student consumption behavior, a data-driven framework for screening student loan eligibility was developed using K-means clustering analysis and decision tree models.

OK, I really think we have entered the Beanie Babies era of dog toys. Some toys drop with a holiday outfit or a limited print, and suddenly they have an energy about them that feels collectible. It ...

Dr. James McCaffrey presents a complete end-to-end demonstration of decision tree regression from scratch using the C# language. The goal of decision tree regression is to predict a single numeric ...

Objective: To evaluate the utility and effectiveness of the recombinant Mycobacterium tuberculosis fusion protein (EC) skin test for tuberculosis (TB) screening among student populations in ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Decision-making during the early stages of research and development (R&D) should be ...

Researchers have developed a new computer-aided diagnosis (CAD) system, BREAST-CAD, to improve breast cancer detection accuracy using machine learning algorithms and a real-time client-server ...

Computer vision systems combined with machine learning techniques have demonstrated success as alternatives to empirical methods for classification and selection. This study aimed to classify tomatoes ...