This version has some minor bug fixes, plus some new features.
* The exact=TRUE option in predict and coef methods now works.
In earlier versions of glmnet, if you supplied a value of s different from the
sequence of lambdas used to compute the fit, predict used interpolation.
This is exact for lasso (alpha=1) and family="gaussian", and an
approximation
otherwise.
Outside the range it used the closest member in the range.
The most frequent value requested was typically s=0,
and that was a) never in the range, and b) always a little off.
Now predict.glmnet returns the exact values
In case you missed earlier announcements, glmnet now has additional families.
* "mgaussian" is a multi-response gaussian model, that uses a group
lasso penalty
for the set of coefficients for each predictor.
* For the type="multinomial" family, there is an additional argument
type.multinomial=c("ungrouped","grouped")
For the grouped cases, again a group lasso penalty is used on the set of class
coefficients
for a predictor.
Trevor Hastie
----------------------------------------------------------------------------------------
Trevor Hastie hastie at stanford.edu
Professor, Department of Statistics, Stanford University
Phone: (650) 725-2231 Fax: (650) 725-8977
URL: http://www.stanford.edu/~hastie
address: room 104, Department of Statistics, Sequoia Hall
390 Serra Mall, Stanford University, CA 94305-4065
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