python利用SVM做手写体识别

from sklearn.datasets import load_digits

digits = load_digits()

print digits.data.shape

from sklearn.cross_validation import train_test_split

X_train, X_test, y_train, y_test = train_test_split(digits.data, digits.target, test_size = 0.25, random_state = 33)

print y_train.shape
print y_test.shape

from sklearn.preprocessing import StandardScaler
from sklearn.svm import LinearSVC

ss = StandardScaler()

X_train = ss.fit_transform(X_train)
X_test = ss.transform(X_test)

lsvc = LinearSVC()
lsvc.fit(X_train, y_train)
y_predict = lsvc.predict(X_test)

print 'The Accuracy of Linear SVC is: ', lsvc.score(X_test, y_test)

from sklearn.metrics import classification_report

print classification_report(y_test, y_predict, target_names = digits.target_names.astype(str))