Abstract: Feature extraction and selection in the presence of nonlinear dependencies among the data is a fundamental challenge in unsupervised learning. We propose using a Gram-Schmidt (GS) type ...
AI transforms cybersecurity. Our AI-driven systems anticipate threats, adapt to your environment, and safeguard your data with privacy at its core, before breaches occur. Innovation in machine ...
If you’ve ever felt frustrated by Spotify‘s algorithm recommending songs that don’t match your taste, there’s some good news. The streaming giant is finally giving you a way to take control of its ...
Feature engineering transforms raw data into the specific inputs that machine learning models need to make accurate predictions. Learn how this crucial process can make the difference between a ...
ABSTRACT: In today’s digital background, sentiment analysis has become an essential factor of Natural Language Processing (NLP), offering valuable insights from vast online data sources. This paper ...
1 Department of Computing Science, Faculty of Science, University of Alberta, Edmonton, AB, Canada 2 Computer Science Department, Faculty of Geology, University of Oviedo, Oviedo, Spain The ...
ABSTRACT: Doping is an issue associated with elite sports as athletes attempt to enhance their performance to gain an edge over other athletes. However, the prevalence of doping is continuously ...
Abstract: In modern healthcare, predicting diseases and identifying their underlying causes are crucial areas of study. This paper proposes a novel feature selection method based on entropy scores and ...
Patent applications on artificial intelligence and machine learning have soared in recent years, yet legal guidance on the patentability of AI and machine learning algorithms remains scarce. The US ...
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