本文整理汇总了Python中NeuralNetwork.NeuralNetwork.initTheta方法的典型用法代码示例。如果您正苦于以下问题：Python NeuralNetwork.initTheta方法的具体用法？Python NeuralNetwork.initTheta怎么用？Python NeuralNetwork.initTheta使用的例子？那么, 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NeuralNetwork.NeuralNetwork的用法示例。
在下文中一共展示了NeuralNetwork.initTheta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: __init__
# 需要导入模块: from NeuralNetwork import NeuralNetwork [as 别名]
# 或者: from NeuralNetwork.NeuralNetwork import initTheta [as 别名]
#.........这里部分代码省略.........
self.test(training_data, "training")
self.test(testData, "testing")
iteration -= testSize
if iteration > 0:
self.clf.train(iteration, batchSize)
totalIter += iteration
print "---------- Settings ----------"
print "Examples :", training_data.shape[0]
print "Batch size :", batchSize
print "Alpha :", self.clf.getAlpha()
print "Momentum factor :", momentumFactor
print "# of Nodes in all layers :", nodeNum
print "Training iteration so far:", totalIter
self.file.write("\n")
self.file.write("---------- Settings ----------" + "\n")
self.file.write("Examples : " + str(training_data.shape[0]) + "\n")
self.file.write("Batch size : " + str(batchSize) + "\n")
self.file.write("Alpha : " + str(self.clf.getAlpha()) + "\n")
self.file.write("Momentum factor : " + str(momentumFactor) + "\n")
self.file.write("# of Nodes in all layers : " + str(nodeNum) + "\n")
self.file.write("Training iteration so far: " + str(totalIter) + "\n")
self.test(training_data, "training")
self.test(testData, "testing")
iteration = 0
print ""
restart = raw_input("Do you want to restart? (Y/N)")
if restart.upper() == "Y":
totalIter = 0
print "Current Alpha is", self.clf.getAlpha()
alpha = raw_input("What alpha ?")
self.clf.setAlpha(float(alpha))
self.clf.initTheta()
self.file.write("\n")
self.file.write("*****************************************************\n")
self.file.write("Re-initialize trail with alpha = " + str(alpha) + "\n")
self.file.write("*****************************************************\n")
print ""
iteration = raw_input("How many iteration do you want to train the model?")
try:
iteration = int(iteration)
except:
iteration = raw_input("Please input an integer")
iteration = 1
print "Total training iterations:", totalIter
def predict(self, data):
"""
"""
return self.clf.predict(data)
def test(self, test_data, mode):
"""
"""
correct = 0
countPrediction = {}
countCorrect = {}
countTotal = Counter(list(test_data[:, 0]))
allPrediction = {}
labels = np.unique(test_data[:, 0])
for label in labels: