数据挖掘——多层感知器手写体识别的Python实现

# coding=utf-8

from sklearn.datasets import load_digits
from sklearn.cross_validation import train_test_split, cross_val_score
from sklearn.pipeline import Pipeline
from sklearn.preprocessing import StandardScaler
from sklearn.neural_network.multilayer_perceptron import MultilayerPerceptronClassifier

if __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)