本文整理汇总了Python中rbm.RBM._mean_hiddens方法的典型用法代码示例。如果您正苦于以下问题：Python RBM._mean_hiddens方法的具体用法？Python RBM._mean_hiddens怎么用？Python RBM._mean_hiddens使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类rbm.RBM的用法示例。
在下文中一共展示了RBM._mean_hiddens方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: fit_network
# 需要导入模块: from rbm import RBM [as 别名]
# 或者: from rbm.RBM import _mean_hiddens [as 别名]
def fit_network(self, X, labels=None):
if labels is None:
labels = numpy.zeros((X.shape[0], 2))
self.layers = []
temp_X = X
for j in range(self.num_layers):
print "\nTraining Layer %i" % (j + 1)
print "components: %i" % self.components[j]
print "batch_size: %i" % self.batch_size[j]
print "learning_rate: %0.3f" % self.learning_rate[j]
print "bias_learning_rate: %0.3f" % self.bias_learning_rate[j]
print "epochs: %i" % self.epochs[j]
print "Sparsity: %s" % str(self.sparsity_rate[j])
print "Sparsity Phi: %s" % str(self.phi)
if j != 0:
self.plot_weights = False
model = RBM(n_components=self.components[j], batch_size=self.batch_size[j],
learning_rate=self.learning_rate[j], regularization_mu=self.sparsity_rate[j],
n_iter=self.epochs[j], verbose=True, learning_rate_bias=self.bias_learning_rate[j],
plot_weights=self.plot_weights, plot_histograms=self.plot_histograms, phi=self.phi)
if j + 1 == self.num_layers and labels is not None:
model.fit(numpy.asarray(temp_X), numpy.asarray(labels))
else:
model.fit(numpy.asarray(temp_X))
temp_X = model._mean_hiddens(temp_X) # hidden layer given visable units
print "Trained Layer %i\n" % (j + 1)
self.layers.append(model)