Synthetic medical data, typically used to address privacy restrictions or to balance underrepresented cases in training data, ...

Abstract: Data discretization plays a critical role in enhancing the performance of the naive Bayes classifier. Traditional data discretization methods often utilize a two-stage framework, where data ...

Compressing data is nothing new when it comes to computing ... It is a major undertaking, bringing together researchers with a broad range of backgrounds, including computational physics and sciences, ...

My name is Sole, the leading instructor at Train in Data and the maintainer of Feature-engine, and together with a group of passionate data scientists and software developers, we maintain and expand ...

School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA ...

2021c). Moreover, to reduce the disadvantageous effects on the model caused by data discretization, reclassification was performed for the 13 continuous variables, including elevation, slope, degree ...