[pymvpa] Using PLR with multiclass

[Swaroop Guntupalli]

Does it help if you assign targets in your sample attributes to {0,1}
instead?

On Wed, Mar 1, 2017 at 1:13 PM, Neal Morton <mortonne at gmail.com> wrote:

> Is there a way to use PLR with a multiclass problem? When I try to use the
> MulticlassClassifier, that produces binary labels with -1 and 1. But PLR
> expects 0 and 1.
>
>
>
> The classifier is created like so:
>
>
>
> from mvpa2.clfs.plr import PLR
>
> from mvpa2.clfs.meta import MulticlassClassifier
>
> clf = MulticlassClassifier(PLR(lm=10))
>
>
>
> When I try to train the classifier on an fMRI dataset with four classes, I
> get:
>
>
>
> Traceback (most recent call last):
>
>   File "/home1/03206/mortonne/analysis/bender/mvpa/loc_xval_diag.py",
> line 98, in <module>
>
>     clf.train(ds1)
>
>  File "/work/IRC/ls5/lib/python2.7/site-packages/mvpa2/base/learner.py",
> line 137, in train
>
>     self._train(ds)
>
>   File "/work/IRC/ls5/lib/python2.7/site-packages/mvpa2/clfs/meta.py",
> line 1165, in _train
>
>     CombinedClassifier._train(self, dataset)
>
>   File "/work/IRC/ls5/lib/python2.7/site-packages/mvpa2/clfs/meta.py",
> line 628, in _train
>
>     BoostedClassifier._train(self, dataset)
>
>   File "/work/IRC/ls5/lib/python2.7/site-packages/mvpa2/clfs/meta.py",
> line 118, in _train
>
>     clf.train(dataset)
>
>   File "/work/IRC/ls5/lib/python2.7/site-packages/mvpa2/base/learner.py",
> line 137, in train
>
>     self._train(ds)
>
>   File "/work/IRC/ls5/lib/python2.7/site-packages/mvpa2/clfs/meta.py",
> line 1053, in _train
>
>     self.clf.train(datasetselected)
>
>   File "/work/IRC/ls5/lib/python2.7/site-packages/mvpa2/base/learner.py",
> line 137, in train
>
>     self._train(ds)
>
>   File "/work/IRC/ls5/lib/python2.7/site-packages/mvpa2/clfs/plr.py",
> line 76, in _train
>
>     %(set(d),)
>
> ValueError: Regressors for logistic regression should be [0,1]. Got
> set([1, -1])
>
>
>
>
>
> I have the latest versions of meta.py and plr.py. There was a change
> <https://github.com/PyMVPA/PyMVPA/issues/37> in PLRWeights to support
> different values of labels, but that change doesn’t seem to have affected
> the PLR classifier.
>
>
>
> Thanks,
>
> Neal
>
>
>
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