Abstract: Feature selection in a traditional binary classification algorithm is always used in the stage of dataset preprocessing, which makes the obtained features not necessarily the best ones for ...

Explore the first part of our series on sleep stage classification using Python, EEG data, and powerful libraries like Sklearn and MNE. Perfect for data scientists and neuroscience enthusiasts!

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 = ...

This study presents data on sex differences in gene expression across organs of four mice taxa. The authors have generated a unique and convincing dataset that fills a gap left by previous studies.

The Large-ness of Large Language Models (LLMs) ushered in a technological revolution. We dissect the research. The Large-ness of Large Language Models (LLMs) ushered ...

Binary options let investors predict asset price movements for a fixed payout. Investors know potential gain or loss upfront, simplifying risk management. Example: Predicting a stock price increase ...

1 Department of Computer Studies, Arab Open University, Riyadh, Saudi Arabia 2 Department of Computer Sciences, ISSAT, University of Gafsa, Gafsa, Tunisia Cybersecurity has become a significant ...

Abstract: The binary classification problem is a fundamental and core problem type in machine learning, and many machine learning algorithms, such as logistic regression and tree models, are widely ...

1 Department of Mathematical Sciences, Sol Plaatje University, Kimberley, South Africa 2 Department of Computer Science and Information Technology, Sol Plaatje University, Kimberley, South Africa Deep ...