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
Corex featurization and modeling primitives for D3M envrionments
Featurization: (featurization with information regularization for continuous data (linear Gaussian model) and text (similar to LDA)) Corex continuous Corex text
Regression: (echo provides mutual information regularization: linear regression and neural network modeling primitives provided) EchoLinear EchoRegression EchoClassification
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
dsbox_corex-1.1.1.tar.gz
(64.1 kB
view hashes)
Built Distribution
Close
Hashes for dsbox_corex-1.1.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 1198fdb2c0c3754ccde004cd4f123ded121ae17a47f9fc03758384a1b5a518b8 |
|
MD5 | 9aad28554037c32811480c9a191673e3 |
|
BLAKE2b-256 | ac4e597b867bd8d66db69bf52f66fc9e3b8cf59371bb3c2c41ac7b3ed01c85da |