scikit-learn/scikit-learn — pull request #1300 by GaelVaroquaux (2012-10-31 09:36:02+00:00)
Title: WIP: Lars drop for good

For ill-conditioned design, this implements the strategy suggested by @fabianp and used in R to drop heavily correlated regressors.

This is a continuation of PR #1238, with a rebase and an addition of the new strategy.

However, there are two issues, one is that the X matrix is not full rank (has degenerate regressors) and that the lars cannot make good choices. The other one is that at the end of the path, numerical errors are bigger than the max residual, and thus no good path can be computed. This is seen because alpha than increases in the path. It tells us that it is time to stop the path.

This PR deals with both issues, and it solves the issue reported on the mailing list by Alejandro Weinstein and @NelleV
http://sourceforge.net/mailarchive/message.php?msg_id=29927302

@fabianp, @agramfort please review :)