Background Suicide rates have increased over the last couple of decades globally, particularly in the United States and among populations with lower economic status who present at safety-net ...
ML powered system that predicts most suitable crop using ensemble(hard voting) of Decision Tree, Random Forest, and Gradient Boosting models implemented from scratch ...
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.
After receiving his degree in Journalism & Media Communications from CSU in 2019, Erik began building his career in online media, and found his dream job when he joined Game Rant as a staff writer.
Background: Decisions surrounding involuntary psychiatric treatment orders often involve complex clinical, legal, and ethical considerations, especially when patients lack decisional capacity and ...
Abstract: The study aims to improve the accuracy of cyberbullying detection. Compared to the Random Forest classifier, utilize XGBoost to improve accuracy. In this study, two groups were compared. The ...
A novel framework integrates urban surveillance video data with a two-stage AI pipeline: an enhanced random forest classifier detects rain streaks and selects key image regions, while a hybrid deep ...
ABSTRACT: The Efficient Market Hypothesis postulates that stock prices are unpredictable and complex, so they are challenging to forecast. However, this study demonstrates that it is possible to ...
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.
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