ABSTRACT: Atrial fibrillation (AF) is a leading cardiac arrhythmia associated with elevated mortality risk, particularly in low-resource settings where early risk stratification remains challenging.
Abstract: This paper proposes a Random Forest (RF) machine learning algorithm-based prediction model for the state of charge (SoC) level of lithium-ion batteries for electric vehicles. To show the ...
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.
ABSTRACT: The stock market faces persistent challenges, including inefficiencies, volatility, and barriers to entry, which hinder its accessibility and reliability for investors. This paper explores ...
Numbers are No. (%) unless otherwise noted. ACE indicates angiotensin-converting enzyme; ARB, angiotensin receptor blocker; DPP-4, dipeptidyl peptidase-4; GLP-1, glucagon-like peptide-1; PCSK9, ...
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 ...
An Efficient Random Forest Classifier for Detecting Malicious Docker Images in Docker Hub Repository
Abstract: The number of exploits of Docker images involving the injection of adversarial behaviors into the image’s layers is increasing immensely. Docker images are a fundamental component of Docker.
This study introduces a sophisticated intelligent predictive maintenance system for industrial conveyor belts powered by a random forest machine learning model. The random forest model was evaluated ...
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