corexcontinuous

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.

These details have not been verified by PyPI

Project links

Project description

The author of this package has not provided a project description

Project details

These details have not been verified by PyPI

Project links

Release history Release notifications | RSS feed

0.2.8

Jan 26, 2018

0.2.7

Jan 25, 2018

0.2.6

Jan 25, 2018

0.2.5

Jan 18, 2018

0.2.4

Jan 18, 2018

0.2.3

Jan 18, 2018

0.2.2

Jan 18, 2018

This version

0.2.1

Dec 23, 2017

0.1.11

Dec 22, 2017

0.1.10

Dec 22, 2017

0.1.9

Dec 22, 2017

0.1.8

Oct 20, 2017

0.1.7

Oct 4, 2017

0.1.6

Sep 27, 2017

0.1.5

Sep 21, 2017

0.1.4

Sep 20, 2017

0.1.3

Sep 12, 2017

0.1.2

Sep 1, 2017

Download files

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

Source Distribution

corexcontinuous-0.2.1.tar.gz (84.8 kB view details)

Uploaded Dec 23, 2017 Source

File details

Details for the file corexcontinuous-0.2.1.tar.gz.

File metadata

Download URL: corexcontinuous-0.2.1.tar.gz
Upload date: Dec 23, 2017
Size: 84.8 kB
Tags: Source
Uploaded using Trusted Publishing? No

File hashes

Hashes for corexcontinuous-0.2.1.tar.gz
Algorithm	Hash digest
SHA256	`325f93da663b740d02754d8c4e2460660b6fb2baf1ad28373d86d2918662edf0`
MD5	`26e2f96496e3570a68c421653d98de0c`
BLAKE2b-256	`161f888e815337c353e6d7b6aef449f338bc87419b760fc4050511212e9565a2`