Background: Heart failure (HF), with its distinct phenotypes, poses significant public health challenges. Early diagnosis of specific HF phenotypes is crucial for timely therapeutic intervention.

Abstract: Random forest (RF) is widely regarded as one of the most prevalent machine learning algorithms. To achieve higher precision, the structure of decision trees that serve as base learners in RF ...

ABSTRACT: This study presents a comparative analysis of machine learning models for threat detection in Internet of Things (IoT) devices using the CICIoT2023 dataset. We evaluate Logistic Regression, ...

Open the VS Code software on your computer and then click the Greater Than-Less Than arrow sign on the bottom left side. Now, select the Tunnel option. It will take a few seconds to install the Tunnel ...

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: Heart disease is a major health concern, and this study investigates how machine learning, particularly Random Forest (RF), can be used to identify it early and assess risk. We tested ...

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 ...