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

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 ...

Introduction: Accurate identification of forest tree species is essential for sustainable forest management, biodiversity assessment, and environmental monitoring. Urban forests, in particular, ...

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 ...

Introduction: The unmanned aerial vehicle -based light detection and ranging (UAV-LiDAR) can quickly acquire the three-dimensional information of large areas of vegetation, and has been widely used in ...

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 ...

1 Department of Computer Engineering, Northeastern University, Boston, USA. 2 Department of Computer Science, Rochester Institute of Technology, Rochester, USA. 3 Department of Computer Engineering, ...