def train(self, training_set_inputs, training_set_outputs, number_of_training_iterations):
for iteration in xrange(number_of_training_iterations):
output = self.think(training_set_inputs)
error = training_set_outputs - output
adjustment = dot(training_set_inputs.T, error * self.__sigmoid_derivative(output))
self.synaptic_weights += adjustment
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