IEEE

Enhancing Prediction Accuracy Through Random Forest in Classification and Regression

Abstract: Random Forest is a well-known type of ensemble learning, which combines a number of decision trees to improve the prediction ability and reduce the risk of overfitting. This paper aims at ...
Frontiers

Satellite-based monitoring of forage quality in grasslands of the United Kingdom using sentinel-2 data and random forest regression

Introduction: In the temperate grasslands of the UK, forage quality is a key factor influencing both animal performance and environmental impact. Because forage quality strongly affects rumen ...
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How to create a modern four-story mud villa in the heart of the forest

In this video, we take you through the entire process of building the most creative contemporary four-story mud villa in the forest. From the initial concept to the final touches, we show you how we ...
Frontiers

Enhanced risk prediction of femoral head osteonecrosis in the elderly: a comparative study of random forest and logistic regression models

Department of Orthopedics, Shanxi Bethune Hospital, Tongji Shanxi Hospital, Shanxi Academy of Medical Sciences, Third Hospital of Shanxi Medical University, Taiyuan, China Background and aim: ...
IEEE

Evaluating the Performance of Random Forest Regression in Predicting Electric Motor Temperature

Objective: This research applies Random Forest Regression(RFR) as a non-linear technique to forecast temperature based on multiple input parameters, including motor load, speed, and ambient ...