ITK
4.1.0
Insight Segmentation and Registration Toolkit
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00001 /*========================================================================= 00002 * 00003 * Copyright Insight Software Consortium 00004 * 00005 * Licensed under the Apache License, Version 2.0 (the "License"); 00006 * you may not use this file except in compliance with the License. 00007 * You may obtain a copy of the License at 00008 * 00009 * http://www.apache.org/licenses/LICENSE-2.0.txt 00010 * 00011 * Unless required by applicable law or agreed to in writing, software 00012 * distributed under the License is distributed on an "AS IS" BASIS, 00013 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 00014 * See the License for the specific language governing permissions and 00015 * limitations under the License. 00016 * 00017 *=========================================================================*/ 00018 #ifndef __itkIterativeSupervisedTrainingFunction_h 00019 #define __itkIterativeSupervisedTrainingFunction_h 00020 00021 #include "itkTrainingFunctionBase.h" 00022 00023 namespace itk 00024 { 00025 namespace Statistics 00026 { 00033 template<class TSample, class TTargetVector, class ScalarType> 00034 class IterativeSupervisedTrainingFunction : public TrainingFunctionBase<TSample, TTargetVector, ScalarType> 00035 { 00036 public: 00037 00038 typedef IterativeSupervisedTrainingFunction Self; 00039 typedef TrainingFunctionBase<TSample, TTargetVector, ScalarType> Superclass; 00040 typedef SmartPointer<Self> Pointer; 00041 typedef SmartPointer<const Self> ConstPointer; 00042 00044 itkTypeMacro(IterativeSupervisedTrainingFunction, TrainingFunctionBase); 00045 00047 itkNewMacro(Self); 00048 00049 typedef typename Superclass::NetworkType NetworkType; 00050 typedef typename Superclass::InternalVectorType InternalVectorType; 00051 00052 void SetNumOfIterations(SizeValueType i); 00053 00054 virtual void Train(NetworkType* net, TSample* samples, TTargetVector* targets); 00055 00056 itkSetMacro(Threshold, ScalarType); 00057 00058 protected: 00059 00060 IterativeSupervisedTrainingFunction(); 00061 virtual ~IterativeSupervisedTrainingFunction(){}; 00062 00064 virtual void PrintSelf( std::ostream& os, Indent indent ) const; 00065 00066 ScalarType m_Threshold; 00067 bool m_Stop; //stop condition 00068 }; 00069 00070 } // end namespace Statistics 00071 } // end namespace itk 00072 00073 #ifndef ITK_MANUAL_INSTANTIATION 00074 #include "itkIterativeSupervisedTrainingFunction.hxx" 00075 #endif 00076 00077 #endif 00078