Hi Mathias.
As far as I know the use of class weights in grid search is not possible
in SVC at the moment. It can be used as a parameter to fit, but this
prevents one from using it for grid searches.
This is a known issue and the class_weight should be moved to
the initialization of SVC.
I am (somewhat) working on this.

Cheers,
Andy


On 02/03/2012 01:23 PM, Mathias Verbeke wrote:
Hi Olivier,

That's something I tried already, but then I get:

AssertionError: Invalid parameter class_weight for estimator SVC

Any idea what can be wrong?

Thanks,

Mathias


On Fri, Feb 3, 2012 at 12:19 PM, Olivier Grisel <[email protected] <mailto:[email protected]>> wrote:

    2012/2/3 Mathias Verbeke <[email protected]
    <mailto:[email protected]>>:
    > Hi Adreas,
    >
    > Thanks a lot; that answers my questions. Just a quick check to
    be sure I
    > understand it correctly: the results in the classification
    report for the
    > best classifier are the ones on the test set, right?

    It print the performance measured on the test set (also known as
    evaluation set) of the best classifier as found on the training set
    (also known as development set).

    If you do the parameter selection and evaluation on the same dataset
    you will be likely to overfit the hyperparameters settings and hence
    your performance estimation will be an over-estimate of the true
    generalization performance.

    > And another small question: could you tell me how/where I need
    to set the
    > class_weight parameter, since this doesn't seem to work in the
    regular way
    > in the fit method? Would it furthermore be possible to - besides
    'auto' -
    > tune this as well with GridSearch?

    You can extend the grid search as follows (that will double the
    running time):

    tuned_parameters = [
       {'kernel': ['rbf'], 'gamma': [1e-3, 1e-4],
        'C': [1, 10, 100, 1000], 'class_weight': [None, 'auto']},
       {'kernel': ['linear'], 'C': [1, 10, 100, 1000],
        'class_weight': [None, 'auto']}
    ]

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

    
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