Abstract: This study addresses the lack of comprehensive evaluations of feature scaling by systematically assessing 12 techniques, including less common methods such as VAST and Pareto, in 14 machine ...

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...

This study presents a potentially valuable exploration of the role of thalamic nuclei in language processing. The results will be of interest to researchers interested in the neurobiology of language.

Abstract: The most important step in data processing is handling missing data. Missing data introduces bias and degrades machine learning's model performance. Traditional imputation techniques, such ...