IEEE

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.

Predictive Modeling: Techniques, Uses, and Key Takeaways

Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.
Frontiers

Using a random forest model to predict volume growth of larch, birch, and their mixed forests in northern China

Accurately quantifying forest volume and identifying its driving mechanisms are critical for achieving carbon neutrality objectives. Using data from the National Forest Inventory (NFI), plot-level ...
IEEE

Machine Learning Approaches for Loan Default Prediction: A Comparative Analysis of Random Forest and KNN Algorithms

One of the key issues faced by financial institutions is the prediction of loan default. Two machine learning methods, Random Forest and K-Nearest Neighbors (KNN), are tested in this study, using an ...