这里显示 数字识别 使用scikit-learn
from scipy import io as spio
import numpy as np
from sklearn.linear_model import LogisticRegression
data = spio.loadmat("../data/2-logistic_regression/data_digits.mat")
X = data['X'] # 获取X数据，每一行对应一个数字20x20px
y = data['y'] # 这里读取mat文件y的shape=(5000, 1)
y = np.ravel(y) # 调用sklearn需要转化成一维的(5000,)
model = LogisticRegression()
model.fit(X, y) # 拟合
predict = model.predict(X) # 预测
print (u"预测准确度为：%f%%" % np.mean((predict == y)*100))
预测准确度为：94.380000%