基于Python的深度信念网络程序

# -*- coding: utf-8 -*-
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Created on Sat Apr 21 12:05:28 2018

@author: Administrator
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import numpy as np
from keras.models import Sequential
from keras.layers import Dense
from keras.optimizers import SGD
from keras import regularizers
from sklearn.neural_network import BernoulliRBM
import matplotlib.pyplot as plt

class DBN（）:
    def __init__（
            self
            x_train
            y_train
            x_test
            y_test
            hidden_layer
            learning_rate_rbm=0.0001
            batch_size_rbm=100
            n_epochs_rbm=30
            verbose_rbm=1
            random_seed_rbm=1300
            activation_function_nn=‘relu‘
            learning_rate_nn=0.005
            batch_size_nn=100
            n_epochs_nn=10
            verbose_nn=1
            decay_rate=0）:

            self.x_train = x_train
            self.y_train = y_train
            self.x_test = x_test
            self.y_test =