Cybercriminals and cybersecurity are a cat-and-mouse pair. Only that at different times they keep swapping their roles. This ...

Researchers have developed a new "emotionally aware" AI-based model for classifying mental health conditions, which could ...

James Talarico on CNN defended his claim on God being non-binary is accurate: Trump revisits idea to annex Canada and make it the 51st state, days after Carney calls for new partnership with US Never ...

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...

ABSTRACT: Accurate prediction of malaria incidence is indispensable in helping policy makers and decision makers intervene before the onset of an outbreak and potentially save lives. Various ...

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.

Physical frailty is a pressing public health issue that significantly increases the risk of disability, hospitalization, and mortality. Early and accurate detection of frailty is essential for timely ...

Abstract: Multiclass classification problems are often addressed by decomposing them into a set of binary classification tasks. A critical step in this approach is the effective aggregation of ...

There has been growing attention to multi-class classification problems, particularly those challenges of imbalanced class distributions. To address these challenges, various strategies, including ...

Abstract: In this study, a novel approach for solving the PU learning problem is proposed based on an anomaly detection strategy. A Convolutional Autoencoder (CAE) is used to extract latent encodings ...