In order to apply the random forest regression algorithm to the structural optimization of concrete frames, this paper uses the relative dynamic elastic modulus as the evaluation index of the concrete ...

Random forest is a popular and powerful machine learning algorithm that can handle both classification and regression problems. It is based on the idea of creating a large number of decision trees ...

Our analysis revealed that Random Forest consistently outperformed other models in balancing predictive accuracy and alignment with financial forecasts. Among the tested configurations, the ...

This repository contains implementations of the Random Cut Forest (RCF) probabilistic data structure. RCFs were originally developed at Amazon to use in a nonparametric anomaly detection algorithm for ...

Nature. Decision Tree: A single decision tree structure used in making decisions based on features of the dataset. Random Forest: An ensemble of multiple decision trees that combine the output for ...

Random forest or random decision forest is a tree-based ensemble learning method for classification and regression in the data science field. There are various fields like banking and e-commerce where ...

Ensemble methods like Random Forest, Decision Tree, XGboost algorithms have shown very good results when we talk about classification. These algorithms give high accuracy at fast speed. Both the two ...