diff --git a/include/NeuralNetwork/ConstructiveAlgorithms/CascadeCorrelation.h b/include/NeuralNetwork/ConstructiveAlgorithms/CascadeCorrelation.h
index c3daf1c..278ea31 100644
--- a/include/NeuralNetwork/ConstructiveAlgorithms/CascadeCorrelation.h
+++ b/include/NeuralNetwork/ConstructiveAlgorithms/CascadeCorrelation.h
@@ -52,6 +52,8 @@ namespace NeuralNetwork {
 							error = trainOutputs(network, patterns);
 						}
 
+						std::cout << error << "\n";
+
 						if(_prunningStatus && error*1.01 >= lastError) { // it is not getting bettter
 							network.removeLastHiddenNeuron();
 							error=lastError;
diff --git a/include/NeuralNetwork/ProblemSets/Parity.h b/include/NeuralNetwork/ProblemSets/Parity.h
index fe6c106..9965ed5 100644
--- a/include/NeuralNetwork/ProblemSets/Parity.h
+++ b/include/NeuralNetwork/ProblemSets/Parity.h
@@ -6,15 +6,15 @@ namespace NeuralNetwork {
 	namespace ProblemSets {
 		typedef std::pair<std::vector<float>, std::vector<float>> TrainingPattern;
 
-		std::vector<TrainingPattern> Parity3() {
+		std::vector<TrainingPattern> Parity3(float min = 0.0) {
 			return {
-				{{0,0,0},{0}},
-				{{0,0,1},{1}},
-				{{0,1,0},{1}},
-				{{0,1,1},{0}},
-				{{1,0,0},{1}},
-				{{1,0,1},{0}},
-				{{1,1,0},{0}},
+				{{min,min,min},{min}},
+				{{min,min,1},{1}},
+				{{min,1,min},{1}},
+				{{min,1,1},{min}},
+				{{1,min,min},{1}},
+				{{1,min,1},{min}},
+				{{1,1,min},{min}},
 				{{1,1,1},{1}},
 			};
 		}
diff --git a/src/NeuralNetwork/ConstructiveAlgorithms/CascadeCorrelation.cpp b/src/NeuralNetwork/ConstructiveAlgorithms/CascadeCorrelation.cpp
index 87587dc..66661a6 100644
--- a/src/NeuralNetwork/ConstructiveAlgorithms/CascadeCorrelation.cpp
+++ b/src/NeuralNetwork/ConstructiveAlgorithms/CascadeCorrelation.cpp
@@ -48,7 +48,8 @@ float CascadeCorrelation::trainOutputs(Cascade::Network &network, const std::vec
 	}
 	while(iteration++ < _maxOutputLearningIterations && iterWithoutImporvement < _maxOutputLearningIterationsWithoutChange);
 
-	std::cout << "outputLearning: " << error << ", last: " << lastError << ", iters: " << iteration << "\n";
+//	std::cout << "outputLearning: " << error << ", last: " << lastError << ", iters: " << iteration << "\n";
+
 	for(std::size_t neuron = 0; neuron < outputs; neuron++) {
 		network.getOutputNeurons()[neuron]->setWeights(p[1][neuron + 1].getWeights());
 	}
@@ -144,7 +145,7 @@ float CascadeCorrelation::trainOutputsRandom(std::size_t step, Cascade::Network
 
 	FeedForward::Network &p = *possibleOutputs[bestNetwork];
 
-	std::cout << "network: " << bestNetwork << ", error: " << bestScore << "\n";
+	std::cout << "network: " << bestNetwork << "\n";
 
 	for(std::size_t neuron = 0; neuron < outputs; neuron++) {
 		network.getNeuron(network.getNeuronSize() - outputs + neuron)->setWeights(p[1][neuron + 1].getWeights());