2013/1/8 Ronnie Ghose <[email protected]>:
> Can anyone please tell me what I'm doing wrong?
>
> The example here
> (http://scikit-learn.org/dev/modules/generated/sklearn.grid_search.GridSearchCV.html)
>
>>>> from sklearn import svm, grid_search, datasets
>>>> iris = datasets.load_iris()
>>>> parameters = {'kernel':('linear', 'rbf'), 'C':[1, 10]}
>>>> svr = svm.SVC()
>>>> clf = grid_search.GridSearchCV(svr, parameters)
>>>> clf.fit(iris.data, iris.target)
> ...
> GridSearchCV(cv=None,
>     estimator=SVC(C=1.0, cache_size=..., coef0=..., degree=...,
>         gamma=..., kernel='rbf', max_iter=-1, probability=False,
>         shrinking=True, tol=...),
>     fit_params={}, iid=True, loss_func=None, n_jobs=1,
>         param_grid=...,
>         ...)
>
> gives .98
>
> when i change svr and the parameters:
>
>
>
> from sklearn import svm, grid_search, datasets,linear_model
>
>
> iris = datasets.load_iris()
> parameters = {'alpha':[.0001,.001]}
> sgd = linear_model.SGDRegressor()
> clf = grid_search.GridSearchCV(sgd, parameters)
> clf.fit(iris.data, iris.target)
> print clf.best_score_
>
>
>
>
> suddenly I get
>
>
> Traceback (most recent call last):
>   File "GridSearch_SGDRegressor.py", line 6, in <module>
>     clf.fit(iris.data, iris.target)

This does not really make sense to fit a regressor model on a
classification problem (the integer targets does not have a total
ordering meaning).

>
>   File "/usr/local/lib/python2.7/dist-packages/sklearn/grid_search.py", line
> 415, in fit
>     best_estimator.fit(X, y, **self.fit_params)
> AttributeError: 'NoneType' object has no attribute 'fit'

That looks like a bug. Could you open a new github issue?


--
Olivier
http://twitter.com/ogrisel - http://github.com/ogrisel

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