/** * Create an instance of {@link NeuralNetwork } * */ public NeuralNetwork createNeuralNetwork() { return new NeuralNetwork(); }
NeuralNetwork nnet = new NeuralNetwork(); nnet.setActivationFunction( ACTIVATIONFUNCTION.LOGISTIC ); nnet.setFunctionName( MININGFUNCTION.REGRESSION ); nnet.setNormalizationMethod( NNNORMALIZATIONMETHOD.NONE ); nnet.setModelName( modelName ); nnet.getExtensionsAndNeuralLayersAndNeuralInputs().add( miningSchema ); nnet.getExtensionsAndNeuralLayersAndNeuralInputs().add( outputs ); nnet.getExtensionsAndNeuralLayersAndNeuralInputs().add( nins ); nnet.getExtensionsAndNeuralLayersAndNeuralInputs().add( hidden ); nnet.getExtensionsAndNeuralLayersAndNeuralInputs().add( outer ); nnet.getExtensionsAndNeuralLayersAndNeuralInputs().add( finalOuts );
NeuralNetwork n2 = (NeuralNetwork) net2.getAssociationModelsAndBaselineModelsAndClusteringModels().get( 0 ); assertEquals( n1.getExtensionsAndNeuralLayersAndNeuralInputs().size(), n2.getExtensionsAndNeuralLayersAndNeuralInputs().size() ); assertEquals( 6, n2.getExtensionsAndNeuralLayersAndNeuralInputs().size() ); NeuralLayer l1 = (NeuralLayer) n1.getExtensionsAndNeuralLayersAndNeuralInputs().get( 3 ); NeuralLayer l2 = (NeuralLayer) n2.getExtensionsAndNeuralLayersAndNeuralInputs().get( 3 );
NeuralNetwork n2 = (NeuralNetwork) net2.getAssociationModelsAndBaselineModelsAndClusteringModels().get( 0 ); assertEquals( n1.getExtensionsAndNeuralLayersAndNeuralInputs().size(), n2.getExtensionsAndNeuralLayersAndNeuralInputs().size() ); assertEquals( 6, n2.getExtensionsAndNeuralLayersAndNeuralInputs().size() ); NeuralLayer l1 = (NeuralLayer) n1.getExtensionsAndNeuralLayersAndNeuralInputs().get( 3 ); NeuralLayer l2 = (NeuralLayer) n2.getExtensionsAndNeuralLayersAndNeuralInputs().get( 3 );