Background Suicide rates have increased over the last couple of decades globally, particularly in the United States and among populations with lower economic status who present at safety-net ...

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

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

1 School of Nursing, Naval Medical University, Shanghai, China 2 Department of Clinical Psychology, Chongqing Mental Health Center, Chongqing, Shanghai, China Background: Benefit finding (BF) improves ...

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: The goal of this study is to evaluate how well driver drowsiness can be detected using two different machine learning methods: the Decision Tree Classifier and the Novel Random Forest ...

ABSTRACT: The advent of the internet, as we all know, has brought about a significant change in human interaction and business operations around the world; yet, this evolution has also been marked by ...

Decision trees are a powerful tool for decision-making and predictive analysis. They help organizations process large amounts of data and break down complex problems into clear, logical steps. Used in ...

Decision Tree with PEP,MEP,EBP,CVP,REP,CCP,ECP pruning algorithms,all are implemented with Python(sklearn-decision-tree-prune included,All are finished). Automatic decision tree generation from ...