Skip to main content

Return components/latent factors that explain the most multivariate mutual information in the data under Linear Gaussian model. For comparison, PCA returns components explaining the most variance in the data.

Project description

The author of this package has not provided a project description

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

corexcontinuous-0.2.2.tar.gz (15.4 kB view details)

Uploaded Source

File details

Details for the file corexcontinuous-0.2.2.tar.gz.

File metadata

File hashes

Hashes for corexcontinuous-0.2.2.tar.gz
Algorithm Hash digest
SHA256 58c27c708f3a28cdd14467d2be05b397838fea027e36d20d3fa32893b846d76d
MD5 c1ae6ebf009df1eda8791b8cf1dabfde
BLAKE2b-256 eaec3adb749b5aaeb4efbafa2cec9075d8edb1bb8a866b14de91a4a5f68ac522

See more details on using hashes here.

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