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Benchmark sklearn's SGDClassifier on RCV1-ccat dataset.
Benchmark sklearn's SGDClassifier on RCV1-ccat dataset.
So generate the input files see .
ACC: 0.9479
AUC: 0.9476
3 loops, best of 1: 1.21 s per loop
import svmlight_loader
from sklearn.linear_model import SGDClassifier
from sklearn.utils import shuffle
from sklearn import metrics
X, y = svmlight_loader.load_svmlight_file('../../corpora/rcv1-ccat/train.dat', buffer_mb=500)
X_test, y_test = svmlight_loader.load_svmlight_file('../../corpora/rcv1-ccat/test.dat', n_features=X.shape[1], buffer_mb=500)
X_train, y_train = shuffle(X, y, random_state=0)
del X
del y
clf = SGDClassifier(n_iter=5, alpha=0.00001), y_train)
y_pred = clf.predict(X_test)
print "ACC: %.4f" % metrics.zero_one_score(y_test, y_pred)
print "AUC: %.4f" % metrics.auc_score(y_test, y_pred)
print "%timeit, y_train)"
print "%timeit clf.score(X_test, y_test)"
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