On 01/23/2012 06:59 PM, Andreas wrote:
> On 01/23/2012 05:54 PM, Dimitrios Pritsos wrote:
>> Relate to LinearSVC() and SGDClassifier()
>>
>> I ran both with a subset of my 33k-samples by 30k-features and I am
>> getting a huge difference in results. Is this expected behavour!
>>
>> After 10-fold-cross-validation (using the Defaults as arguments in both
>> cases) I am getting:
>>
>> Accuracy = 44% for SGD
>> Accuracy = 89% for LinearSVC
>>
>>
>> This is the modules I called
>> csvm = svm.LinearSVC()
>> csvm.fit(X, y)
>> csvm.score(crossv_X, crossv_y)
>>
>> sgd = linear_model.SGDClassifier()
>> sgd.fit(X, y)
>> sgd.score(crossv_X, crossv_y)
>>
>>
>>
> This is somewhat expected since SGD has some tuning parameters.
> For example the number of iterations is set to 5 by default afaik.
> Having this higher would probably give you better results.
> Also the parameter alpha should probably be cross-validated, as SGD
> is more sensitive to this then LinearSVC is to the C parameter.
>

THANX! I will play a bit with these params and I will give a feedback in 
case I will have same results to LinearSVC.
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