Implement gradient descent baseline

[ghost]

(originally reported in Trac by @elehack on 2011-03-16 22:40:55)

Implement the gradient descent fitted baseline with regularization described by Koren in Factorization meets the neighborhood. For this ticket, we aren't implementing the whole SVD++ or Asymmetric-SVD mode; we're just learning the regularized baseline.

This will be LeastSquaresPredictor in the org.grouplens.lenskit.baseline package in the lenskit-core project.

Note: This issue has been automatically migrated from Bitbucket
Created by grouplens on 2013-02-01T21:55:10.665857+00:00, last updated: 2013-02-05T21:16:27.708650+00:00

[ghost]

Done and merged.

Note: This comment has been automatically migrated from Bitbucket
Created by @elehack on 2013-02-05T21:15:01.385763+00:00, last updated: None

[ghost]

Michael Ekstrand michael@elehack.net on 2013-01-18 16:24:09 said:

In [changeset:"e27c465b0f87996d49d5456b4c7d11fd4e15ce9e"]:

Merge in the least squares predictor (refs #20)

Note: This comment has been automatically migrated from Bitbucket
Created by grouplens on 2013-02-01T21:55:10.991102+00:00, last updated: None