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.

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for brekelma from gravatar.com brekelma

Unverified details

These details have not been verified by PyPI
Project links
Meta
Classifiers

Project description

The author of this package has not provided a project description

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for brekelma from gravatar.com brekelma

Unverified details

These details have not been verified by PyPI
Project links
Meta
Classifiers

Release history Release notifications | RSS feed

0.2.10

0.2.9

0.2.8

0.2.7

0.2.6

0.2.5

0.2.4

0.2.3

0.2.2

0.2.1

0.2.0

0.1.47

0.1.46

0.1.45

0.1.44

0.1.43

0.1.42

0.1.12

0.1.11

This version

0.1.10

0.1.9

0.1.8

0.1.7

0.1.6

0.1.5

0.1.4

0.1.3

0.1.2

0.1.1

0.1.0

Download files

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

Source Distribution

corextext-0.1.10.tar.gz (15.8 kB view hashes)

Uploaded Source

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