def test_correlation_pso_vs_derivative(self): netPso = self.CLASS(3, 1) net = CascadeNet(3, 1) candidate = self._get_cascade(net) print("Derivative " + str(net._get_candidate_correlations([candidate], DOUBLE_XOR_INPUTS, DOUBLE_XOR_TARGETS))) candidate = self._get_cascade(netPso) print("PSO " + str(netPso._get_candidate_correlations([candidate], DOUBLE_XOR_INPUTS, DOUBLE_XOR_TARGETS)))
def cost_func(parameters): candidate_activations = [] for activation in activations: candidate_activations.append(self._get_output_node_activation_from_activations(parameters, activation)) return -sum(CascadeNet._real_correlations(candidate_activations, errors)) \ + regularizer_coef*numpy.sum(numpy.abs(candidate_activations))
def cost_func(parameters): candidate_activations = [] for activation in activations: candidate_activations.append( self._get_output_node_activation_from_activations( parameters, activation)) return -sum(CascadeNet._real_correlations(candidate_activations, errors)) \ + regularizer_coef*numpy.sum(numpy.abs(candidate_activations))