from sklearn import linear_model

import sklearn.datasets.svmlight_format as svmlight

from sklearn import grid_search

import cPickle

parameters = {'alpha':[.000001,.0000001,.00000001],'n_iter':[5000,10000,15000]}

feat_vecs,labels = svmlight.load_svmlight_file('featureFile.dat')

svr = linear_model.SGDClassifier()

svr.n_jobs = -1

clf = grid_search.GridSearchCV(svr, parameters)

clf.n_jobs = -1

clf.fit(feat_vecs,labels)

print clf.grid_scores_

with open('gridSearch.out', 'w') as fo:

cPickle.dump(clf.grid_scores_,fo)