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 ...

Abstract: On the base of introducing the Decision Tree, this article lists two main algorithms of Decision Tree. After describing the principle of briefly, it reveals the essential idea and the ...

This paper first discusses the storage structure of trees, selects a convenient storage method for solving the nullity of trees, and then applies the relationship between the maximum matching number ...

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 ...

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 ...

Abstract: This paper presents an automatic machine learning (autoML) algorithm to select a decision tree algorithm which is most suitable for the stated requirements by the user for classification.

This project uses Weka to analyze the "Car Evaluation" dataset with decision trees, comparing model performance on 70/30 and 50/50 data splits. It includes accuracy, F1-scores, and decision tree ...

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, ...

Analytics is often associated with online marketing as a way to measure visits to a website and online commerce. Yet as brands increasingly rely on apps and websites to entice customers, they are ...