Decision trees are interpretable supervised learning algorithms used for classification and regression tasks. (33) When predicting LCI data on the level of technical flows, the target values are ...

A decision tree is a non-parametric supervised learning algorithm, which is utilized for both classification and regression tasks. It has a hierarchical, tree structure, which consists of a root node, ...

We will then discuss their application in the algorithms CART and ID3. We will also be discussing C4.5, an extending algorithm from ID3. In the end of the paper, we will give an introduction of ...

The study shows that machine learning and deep learning algorithms can accurately classify tree species using individual tree point clouds, and the operation process of PointMLP is more concise and ...

Machine learning has been a hot topic in artificial intelligence for quite a few good reasons. In the future, the world’s information would be too massive for us to process. Therefore, it will be ...

However, with the rapid development of machine learning in recent years, it be-comes possible to use powerful machine learning algorithms to process and analyze biolog-ical data. Based on the ...

Decision Trees (DT) are popular machine learning models applied to both classification and regression tasks with known training algorithms such as CART [6], C4.5 [7], and boosted trees [8]. With fewer ...