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 ...

For those who care about the future of life on earth and the destiny of our children, there is nothing more frightening than watching the fossil fuel greed-induced blindness of Trump and the MAGA cult ...

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 ...

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 ...

Objectives This study aimed to employ machine learning algorithms to predict the factors contributing to zero-dose children in Tanzania, using the most recent nationally representative data. Design ...

Abstract: This research study applies a Decision Tree Classifier to detect anomalies in IoT networks using the NSL-KDD collection of data, which is a used widely as a benchmark for intruder ...

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 ...