To address this challenge, we analyzed data from the Behavioral Risk Factor Surveillance System (BRFSS) spanning 1995-2017. We developed innovative methods to handle missing data and normalize values.

This article presents a technique for clustering mixed categorical and numeric data using standard k-means clustering implemented using the C# language. Briefly, the source mixed data is preprocessed ...

The technique presented in this article to cluster mixed categorical and numeric data can also be used to cluster strictly categorical data using k-means. The demo uses k = 3 clusters, which is more ...

Encoding categorical data is a process of converting categorical data into integer format so that the data with converted categorical values can be provided to the models to give and improve the ...

LabelEncoder can be used to store values using less disk space. This is simple to use and works well on tree-based algorithms. It cannot work for linear models, SVMs, or neural networks as their data ...