gregversteeg/CorEx
CorEx or "Correlation Explanation" discovers a hierarchy of informative latent factors. This reference implementation has been superseded by other versions below.
This tool helps researchers and analysts uncover hidden patterns and relationships within complex datasets. You provide it with a matrix of integer data, where rows are samples and columns are variables, and it outputs organized clusters of related variables and identifies the underlying 'factors' driving their correlation. This is ideal for scientists, marketers, or anyone working with high-dimensional categorical data.
307 stars. No commits in the last 6 months.
Use this if you need to understand which variables in your dataset are correlated and group them into meaningful, interpretable factors, especially for discrete or categorical data.
Not ideal if your data primarily consists of continuous variables, as this version is designed for integer inputs and lacks advanced features found in newer implementations.
Stars
307
Forks
54
Language
Python
License
GPL-2.0
Last pushed
Jun 02, 2017
Commits (30d)
0
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