The military has introduced a new classification policy for confidential information as part of its efforts to strengthen ...

Patients who experience adverse ocular effects with bisphosphonates have a notably higher risk for osteonecrosis than those who do not experience such events, a large cohort study shows.

Biologists are confronting a problem they thought they had mostly solved: what, exactly, counts as life. A wave of ...

A Palestinian businessman on the persistent humanitarian crisis in the territory, and what he hopes might change.

Abstract: Support vector machines (SVMs) are popular learning algorithms to deal with binary classification problems. They traditionally assume equal misclassification costs for each class; however, ...

Institute for Information Systems (WIN), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany Introduction: The analysis of discrete sequential data, such as event logs and customer ...

This repository contains two basic prediction models: Credit Card Fraud Detection and Titanic Survival Prediction. Both models demonstrate the use of machine learning for binary classification tasks.

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: Many data mining and pattern recognition tasks have a multi-class classification problem at their core. To give satisfactory results in operational contexts, certain applications necessitate ...