Ejemplo n.º 1
0
void SumSquaredErrorTest::test_calculate_generalization_performance(void) {
  message += "test_calculate_generalization_performance\n";

  NeuralNetwork nn;
  DataSet ds;
  SumSquaredError sse(&nn, &ds);

  double generalization_objective;

  // Test

  nn.set();

  nn.construct_multilayer_perceptron();

  ds.set();

  generalization_objective = sse.calculate_generalization_performance();

  assert_true(generalization_objective == 0.0, LOG);
}
void SumSquaredErrorTest::test_calculate_selection_loss(void)
{
   message += "test_calculate_selection_loss\n";

   NeuralNetwork nn;
   DataSet ds;
   SumSquaredError sse(&nn, &ds);

   double selection_objective;

   // Test

   nn.set();

   nn.construct_multilayer_perceptron();

   ds.set();

   selection_objective = sse.calculate_selection_error();
   
   assert_true(selection_objective == 0.0, LOG);
}