In this paper, we present both a binary and multiclass PE malware classification using four classic machine learning algorithms and four deep learning algorithms. We have applied this algorithm on ...

This paper presents a comprehensive machine learning approach for credit score classification, addressing key challenges in financial risk assessment. We propose an optimized CatBoost-based framework ...

However, there are few clustering methods for binary data, which are common in self-reported lifestyle and behavior symptom data, meaning many of these subtypes remain undetected. To address this ...

In the modern world, cyber security is growing in importance. Every day, there are more and more people using the internet, and they are downloading vast amounts of data from various websites onto ...

Higher Education institutions throughout the globe face challenges in maintaining their student retention. Therefore, there is a need of a mechanism to find students who might be susceptible to leave ...

1 Introduction Support vector machines (SVMs), proposed to solve binary classification problems and further extended for regression (Cortes and Vapnik, 1995; Wang et al., 2021), grouping, and ...

The binary classification technique presented in this article uses a single output node with sigmoid () activation and BCELoss () during training. It is possible to view a binary classification ...