Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...

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

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. A ...

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: This study introduces an analog integrated decision tree classifier specifically engineered for real-time machine predictive maintenance while maintaining minimal power usage. Fabricated ...

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 ...

Institute of Translational Medicine at the Department of Health Sciences and Technology, ETH, Zurich 8093, Switzerland Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland ...