Abstract: The aim of this study is to effectively control and analyze the road traffic flow by applying K-means clustering algorithm and decision tree model to optimize the signal configuration, ...

Automated apple harvesting is hindered by clustered fruits, varying illumination, and inconsistent depth perception in complex orchard environments. While deep learning models such as Faster R-CNN and ...

Dr. James McCaffrey presents a complete end-to-end demonstration of decision tree regression from scratch using the C# language. The goal of decision tree regression is to predict a single numeric ...

ABSTRACT: As a highly contagious respiratory disease, influenza exhibits significant spatiotemporal fluctuations in incidence, posing a persistent threat to public health and placing considerable ...

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 ...

WEST LAFAYETTE, Ind. — Trees compete for space as they grow. A tree with branches close to a wall will develop differently from one growing on open ground. Now everyone from urban planners and ...

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 ...

This project carried out in R applies PCA for dimensionality reduction and K-Means for clustering on the IRIS dataset. It includes EDA, PCA variance analysis, and cluster evaluation using ggplot2 and ...