For inpatients with cirrhosis, a machine learning (ML) model using random forest (RF) analysis is superior for prediction of ...

Researchers employed a machine learning technique known as random forest analysis and found that it significantly outperformed traditional methods in predicting which hospitalized patients with ...

Researchers employed a machine learning technique known as random forest analysis and found that it significantly ...

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 effectiveness ...

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.

Therefore, our proposed ethanol concentration determination method for baijiu, integrating manifold learning and ensemble learning through graph-regularized PCA and random forest-based Raman ...

Implementing the Random Forest algorithm within the nDPI (nDPI) framework can enhance the classification of encrypted traffic, enabling more accurate detection of malicious patterns. Future ...

This study explores the application of machine learning algorithms, specifically decision tree and random forest models, to predict house prices within the Indian real estate market. Utilizing a ...