Our analysis revealed that Random Forest consistently outperformed other models in balancing predictive accuracy and alignment with financial forecasts. Among the tested configurations, the ...

Dubbed CURBy, the Colorado University Randomness Beacon produces random numbers on a publicly available website. The randomness can be verified, traced and certified through the team’s implementation ...

Vincent Yaghoubi earned the nickname “Tank” from his father after he spent an afternoon running over opposing players as a five-year old playing Pop Warner football. The Woodberry Forest ...

Benchmarking showed that the proposed approach outperformed support vector machines, random forest algorithms, and BP neural networks in accuracy and interpretability. The system also incorporates a ...

Non-line-of-sight (NLOS) identification is a major challenge for reliable WiFi-based sensing. Existing NLOS identification methods commonly encounter limited statistical features, rely on pre-designed ...

Data Preparation: Removed irrelevant features (id). Handled missing values using mean imputation for the bmi feature. Encoded categorical variables into numerical representations using LabelEncoder.

Abstract: This paper presents a new feature selection method based on the changes in out-of-bag (OOB) Cohen kappa values of a random forest (RF) classifier, which was tested on the automatic detection ...

Random Forest: Random Forest is an ensemble of decision trees trained using bagging (bootstrap aggregating). Each tree is trained on a different subset of the data and features. The final prediction ...

According to CIO’s State of the CIO Survey 2025, 42% of CIOs say AI and ML are their biggest technology priority for 2025. And while actions driven by ML algorithms can give organizations a ...