import mnist_loader 

# Third-party libraries
from sklearn import svm  

def svm_baseline():
    training_data, validation_data, test_data = mnist_loader.load_data() 
    # train
    clf = svm.SVC() 
    clf.fit(training_data[0], training_data[1]) 
    predictions = [int(a) for a in clf.predict(test_data[0])]
    num_correct 
 
= sum(int(a == y) for a, y in zip(predictions, test_data[1]))
    print ("Baseline classifier using an SVM.")
    print ("%s of %s values correct." % (num_correct, len(test_data[1])))

if __name__ == "__main__":
    svm_baseline()
    

SVM：利用SVM算法實現手寫圖片識別(數據集50000張圖片)—Jason niu