In today’s data-driven world, simplicity often wins. One such tool that offers both power and interpretability is the Decision Tree, a fundamental machine learning algorithm that continues to play a ...

In order to improve the accuracy and efficiency of sports training data analysis, this paper proposes an optimized analysis model by combining Iterative Dichotomiser 3 (ID3) decision tree algorithm ...

High-sensitivity C-reactive protein (hs-CRP) is a biomarker of inflammation predicting the incidence of different health pathologies. In this study, we aimed to evaluate the association between ...

This repository contains a simple implementation of the ID3 decision tree learning algorithm in Python. The ID3 algorithm is a popular machine learning algorithm used for building decision trees based ...

Suppose a bank wants to build a credit scoring model to decide whether to approve or deny a loan application based on several factors such as income, credit score, debt-to-income ratio, and employment ...

Abstract: ID3 decision tree is the most extensive method. It can be used to classify, identify and predict data information, and the whole system can be divided into several stages according to its ...

Machine learning holds the potential to solve many real-world problems, but interpretability is a necessary prerequisite for practitioners in high-stakes domains such as medicine and law. Decision ...

Pruning is essential in tree-based machine learning models to mitigate overfitting caused by excessive features and noise. Decision trees utilise a hierarchical structure to effectively partition data ...

In the last decade, a few valuable types of research have been conducted to discriminate fractured zones from non-fractured ones. In this paper, petrophysical and image logs of eight wells were ...

ID3 is a Machine Learning Decision Tree Algorithm that uses two methods to build the model. The two methods are Information Gain and Gini Index.