Nature

Pruning tree forest and re-sampling for class imbalanced problem

Class imbalance remains a critical challenge in machine learning, as it often leads to biased predictions where algorithms disproportionately favor the majority class, resulting in the ...
Nature

Bootstrapping random forest and CHAID for prediction of white spot disease among shrimp farmers

Technology is playing an important role is healthcare particularly as it relates to disease prevention and detection. This is evident in the COVID-19 era as different technologies were deployed to ...
Harvard Business School

Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem

Yang, Mochen, Edward McFowland III, Gordon Burtch, and Gediminas Adomavicius. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach ...
Visual Studio Magazine

Random Forest Regression and Bagging Regression Using C#

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the random forest regression technique (and a variant called bagging regression), where the goal is to ...
Visual Studio Magazine

Random Forest Regression Using C#

Random forest regression is a tree-based machine learning technique to predict a single numeric value. A random forest is a collection (ensemble) of simple regression decision trees that are trained ...