Skip to main content

Hierarchical Feature Selection through Propagation of Uniquely Correlated Entities

Project description

UniCor - Hierarchical Feature Selection through Propagation of Uniquely Correlated Entities

The idea is to utilize the natural hierarchy in high dimensional, hierarchical datasets (like taxonomic hierarchy in microbiome datasets) in order to make them appropriate for a bigger variety of methods through a reduction of their feature space without the loss of relevant information. The UniCor Metric = |fcc| - ffc identifies UNIquely CORrelated eNtities (UNICORNs) with

  • high absolute correlation (feature [cont. target var.] correlation, |fcc|)
  • negative or low uniqueness (average feature feature correlation, ffc)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

unicor-0.1.0.tar.gz (5.9 kB view hashes)

Uploaded Source

Built Distribution

unicor-0.1.0-py3-none-any.whl (6.9 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page