def guess(self, input_array):
inputs = Matrix.fromArray(input_array)
hidden = Matrix.MatrixMultiplication(self.weights_ih, inputs)
hidden.add(self.bias_ih)
Matrix.mapMatrix(hidden, NeuralNetwork.sigmoid)
outputs = Matrix.MatrixMultiplication(self.weights_ho, hidden)
outputs.add(self.bias_ho)
Matrix.mapMatrix(outputs, NeuralNetwork.sigmoid)
return outputs
def FeedForward(self, input_array):
self.inputs = Matrix.fromArray(input_array)
self.hidden = Matrix.MatrixMultiplication(self.weights_ih, self.inputs)
self.hidden.add(self.bias_ih)
Matrix.mapMatrix(self.hidden, NeuralNetwork.sigmoid)
self.outputs = Matrix.MatrixMultiplication(self.weights_ho,
self.hidden)
self.outputs.add(self.bias_ho)
Matrix.mapMatrix(self.outputs, NeuralNetwork.sigmoid)
return self.outputs
def train(self, input_array, targets):
#error = targets - outputs
inputs = Matrix.fromArray(input_array)
hidden = Matrix.MatrixMultiplication(self.weights_ih, inputs)
hidden.add(self.bias_ih)
Matrix.mapMatrix(hidden, NeuralNetwork.sigmoid)
outputs = Matrix.MatrixMultiplication(self.weights_ho, hidden)
outputs.add(self.bias_ho)
Matrix.mapMatrix(outputs, NeuralNetwork.sigmoid)
output_errors = copy.deepcopy(outputs)
output_errors.multiply(-1)
targets = Matrix.fromArray(targets)
output_errors.add(targets)
#print(self.outputs.toArray())
#print(output_errors.toArray())
hidden_weights = Matrix.transpose(self.weights_ho)
hidden_errors = Matrix.MatrixMultiplication(hidden_weights,
output_errors)
#print(hidden_errors.toArray())
gradient = copy.deepcopy(outputs)
Matrix.mapMatrix(gradient, NeuralNetwork.dsigmoid)
gradient.multiply(output_errors)
gradient.multiply(self.lr)
self.bias_ho.add(gradient)
hidden_T = Matrix.transpose(hidden)
weight_ho_deltas = Matrix.MatrixMultiplication(gradient, hidden_T)
self.weights_ho.add(weight_ho_deltas)
hidden_gradient = copy.deepcopy(hidden)
Matrix.mapMatrix(hidden_gradient, NeuralNetwork.dsigmoid)
hidden_gradient.multiply(hidden_errors)
hidden_gradient.multiply(self.lr)
self.bias_ih.add(hidden_gradient)
inputs_T = Matrix.transpose(inputs)
weight_ih_deltas = Matrix.MatrixMultiplication(hidden_gradient,
inputs_T)
self.weights_ih.add(weight_ih_deltas)
