Abstract: This paper compares the performance of ANN models to Random Forests on benchmarking a test dataset against the risk levels of maternal health as low, mid, or high. The features considered ...

Predict and prevent customer churn in the telecom industry with our advanced analytics and Machine Learning project. Uncover key factors driving churn and gain valuable insights into customer behavior ...

DiseaseX is a state-of-the-art healthcare platform that leverages machine learning to provide accurate disease predictions and health analysis. Our platform integrates multiple specialized models to ...

If you’re like me and grew up playing The Forest before switching over to Roblox horror games like DOORS and Dead Rails, you probably raised an eyebrow when 99 Nights in the Forest claimed to be ...

Background: Decisions surrounding involuntary psychiatric treatment orders often involve complex clinical, legal, and ethical considerations, especially when patients lack decisional capacity and ...

The classification models built on class imbalanced data sets tend to prioritize the accuracy of the majority class, and thus, the minority class generally has a higher misclassification rate.

In this study, multi-source remote sensing data and machine learning algorithms were used to delineate the prospect area of remote sensing geological prospecting in eastern Botswana. Landsat 8 remote ...

Abstract: This work explores the Random Forest classifier's effectiveness in analyzing healthcare data for predicting stroke risks. In this study, data preprocessing is done intensively, which ranges ...

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 ...