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## 為什麼他一直說我寫錯?

``````import numpy
import scipy.special
import matplotlib.pyplot

def __init__(self, inputnodes, hiddennodes, outputnodes, learningrate):
self.inodes = inputnodes
self.hnodes = hiddennodes
self.onodes = outputnodes

self.wih = numpy.random.normal(0.0, pow(self.hnodes, -0.5),
(self.hnodes, self.inodes))
self.who = numpy.random.normal(0.0, pow(self.onodes, -0.5),
(self.onodes, self.hnodes))

self.lr = learningrate

self.activation_function = lambda x: scipy.special.expit(x)

pass

def train(self, inputs_list, targets_list):
inputs = numpy.array(inputs_list, ndmin=2).T
targets = numpy.array(targets_list, ndmin=2).T

hidden_inputs = numpy.dot(self.wih, inputs)

hidden_outputs = self.activation_function(hidden_inputs)

final_inputs = numpy.dot(self.who, hidden_outputs)

final_outputs = self.activation_function(final_inputs)

ouput_errors = (target - actual)

hidden_errors = numpy.dot(self.who.T, outputs_errors)

layers
self.who += self.lr * numpy.dot((outputs_errors *
final_outputs * (1.0 - final_outputs)),
numpy.transpose(hidden_outputs))

layers
self.wih += self.lr * numpy.dot((hidden_errors *
hidden_outputs * (1.0 - hidden_outputs)),
numpy.transpose(inputs))

pass
def query(self, inouts_list):
inputs = numpy.array(inputs_list, ndmin=2).T

hidden_inputs = numpy.dot(self.wih, inputs)

hidden_outputs = self.ativation_function(hidden_inputs)

final_inputs = numpy.dot(self.who, hidden_outputs)

final_outputs = self.activation_function(final_inputs)

return final_outputs

input_nodes = 784
hidden_nodes = 200
output_nodes = 10

learning_rate = 1.0

n = neuralNetwork(input_nodes, hidden_nodes, output_nodes,
learning_rate)

training_data_file = open("mnist_dataset/mnist_train.csv", 'r')
training_data_file.close()

epochs = 5

for e in range(epochs):
for record in training_data_list:
all_values = record.split(',')
inputs = (numpy.asfarray(all_values[1:] / 255.0 * 0.99) + 0.01151
targets = numpy.zeros(output_nodes) + 0.01

targets[int(all_values[0])] = 0.99
n.train(inputs, targets)

pass

pass

test_data_file = open("mnist_dataset/mnist_test.csv", 'r')
test_data_file.close()

for record in test_data_list:
all_values = record.split(',')

correct_label = int(all_values[0])

inputs = (numpy.asfarray(all_values[1:] / 255.0 * 0.99) + 1.0

outputs = n.query(inputs)

label = numpy.argmax(outputs)

if (label == correct_label):
scorecard.append(1)

else:
scorecard.append(0)
pass
pass

scorecard_array = numpy.asarray(scorecard)
print("performmance = ", secordcard_array.sum()/scorecard_array.size)
``````
dragonH iT邦超人 5 級 ‧ 2020-06-10 22:38:17 檢舉
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