A decision tree regression system incorporates a set of if-then rules to predict a single numeric value. Decision tree regression is rarely used by itself because it overfits the training data, and so ...

There is indeed a vast literature on the design and analysis of decision tree algorithms that aim at optimizing these parameters. This paper contributes to this important line of research: we propose ...

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

If you happen to be on a Texas highway sometime this summer, and see a 50,000-pound semi truck barreling along with nobody behind the wheel, just remember: A self-driving truck is less likely to kill ...

ML powered system that predicts most suitable crop using ensemble(hard voting) of Decision Tree, Random Forest, and Gradient Boosting models implemented from scratch ...

ABSTRACT: From the perspective of student consumption behavior, a data-driven framework for screening student loan eligibility was developed using K-means clustering analysis and decision tree models.

If you’ve ever tried to build a agentic RAG system that actually works well, you know the pain. You feed it some documents, cross your fingers, and hope it doesn’t hallucinate when someone asks it a ...

Abstract: 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 ...

LOS ANGELES (KESQ) - A Los Angeles federal judge has ruled that the U.S. Fish and Wildlife Service's decision not to provide Endangered Species Act protections for the imperiled Joshua tree is ...