Here’s a look at categorical data, why it’s hard to wrangle, and how it could be useful. Categorical Data 101. There are two main types of data: categorical and numerical. Numerical data, as the name ...

Conclusion. Encoding categorical data is a crucial step in data preprocessing. By converting categorical data into a numeric format, machine learning models can interpret and work more effectively.

Numerical and Categorical Attributes Data Clustering Using K-Modes and Fuzzy K-Modes Most of the existing clustering approaches are applicable to purely numerical or categorical data only, but not ...