数据挖掘——多层感知器手写体识别的Python实现

# coding=utf-8from sklearn.datasets import load_digitsfrom sklearn.cross_validation import train_test_split, cross_val_scorefrom sklearn.pipeline import Pipelinefrom sklearn.preprocessing import StandardScalerfrom sklearn.neural_network.multilayer_perceptron import MultilayerPerceptronClassifierif __name__ == '__main__':    digits = load_digits()    X = digits.data    y = digits.target    pipeline = Pipeline([('ss', StandardScaler()),                         ('mlp', MultilayerPerceptronClassifier(hidden_layer_sizes=[150, 100], alpha=0.1))                         ])    print '准确率：%s' % cross_val_score(pipeline, X, y, n_jobs=1)