Abstract: If an interaction exists in medical and health sciences, a proper statistical approach is required to avoid an erroneous conclusion. For example, different genders may introduce modified ...

1 School of Artificial Intelligence and Information Engineering, Zhejiang University of Science and Technology, Hangzhou, China. 2 School of Sciences, Zhejiang University of Science and Technology, ...

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 ...

R package, implementing a three steps variable selection procedure based on random forests. Initially developed to handle high dimensional data (for which number of variables largely exceeds number of ...

The operation of the power grid is closely related to meteorological disasters. Changes in meteorological conditions may have an impact on the operation and stability of the power system, leading to ...

College of Mathematical and Statistics, Sichuan University of Science and Engineering, Zigong, China. With the rapid development of the global economy and the acceleration of urbanization, ...

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 ...

This repository contains code used to train the Deep Neural Network (DNN) and Random Forest (RF) models from the study "Modelling Tree Biomass Using Direct and Additive Methods with Point Cloud Deep ...

Abstract: Spatiotemporal satellite image fusion (STIF) has been widely applied in land surface monitoring to generate high spatial and high temporal reflectance images from satellite sensors. This ...

Geothermal heat flow (GHF) data measured directly from boreholes are sparse. Purely physics-based models for geothermal heat flow prediction require various simplifications and are feasible only for ...