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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