Abstract: Industrial components are often case hardened to improve their strength and wear characteristics. Traditionally, component samples are collected from the production line at specific ...

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 ...

Inductive Learning Algorithm (ILA) is an iterative and inductive machine learning algorithm that is used for generating a set of classification rules, which produces rules of the form “IF-THEN”, for a ...

Decision tree is an effective supervised learning method for solving classification and regression problems. This article combines the Pearson correlation coefficient with the CART decision tree, ...

Abstract: In mining data streams the most popular tool is the Hoeffding tree algorithm. It uses the Hoeffding's bound to determine the smallest number of examples needed at a node to select a ...

In recent years, artificial intelligence has played an important role in education, wherein one of the most commonly used applications is forecasting students’ academic performance based on personal ...

Machine learning (ML) approaches are a collection of algorithms that attempt to extract patterns from data and to associate such patterns with discrete classes of samples in the data—e.g., given a ...

ABSTRACT: The information gained after the data analysis is vital to implement its outcomes to optimize processes and systems for more straightforward problem-solving. Therefore, the first step of ...

Machine learning algorithms that are both interpretable and accurate are essential in applications such as medicine where errors can have a dire consequence. Unfortunately, there is currently a ...