Abstract: Medical datasets are usually imbalanced, where negative cases severely outnumber positive cases. Therefore, it is essential to deal with this data skew problem when training machine learning ...

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 ...

A comprehensive machine learning project to predict food delivery times for a service like Swiggy, considering multiple factors such as restaurant distance, traffic, weather, and time of day.

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 ...

Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, California 94720, United States Article Views are the COUNTER-compliant sum of full text article ...

Artificial intelligence (AI) and data science (DS) are receiving a lot of attention in various fields. In the educational field, the need for education utilizing AI and DS is also being emerged. In ...

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 ...

Since the reform and opening up of China from the 1980s, there have been significant achievements in its economy and the construction of infrastructure. However, the environmental problems caused by ...