DOC: update doxygen of MachineLearningModel

Code/Learning/otbMachineLearningModel.h

@@ -25,6 +25,40 @@
 
 namespace otb
 {
+
+/** \class MachineLearningModel
+ * \brief MachineLearningModel is the base class for all classifier objects (SVM, KNN,
+ *        Random Forests, Artificial Neural Network, ...) implemented in the supervised classification framework of the OTB.
+ *
+ * MachineLearningModel is an abstract object that specifies behavior and
+ * interface of supervised classifiers (SVM, KNN, Random Forests, Artificial
+ * Neural Network, ...) in the generic supervised classification framework of the OTB.
+ * The main generic virtual methods specifically implemented in each classifier
+ * derived from the MachineLearningModel class are two learning-related methods:
+ * Train() and Save(), and two classification-related methods: Load() and Predict().
+ *
+ * Thus, each classifier derived from the MachineLearningModel class
+ * computes its corresponding model with Train() and exports it with
+ * the help of the Save() method.
+ *
+ * It is also possible to classify any input sample composed of several
+ * features (or any number of bands in the case of a pixel extracted
+ * from a multi-band image) with the help of the Predict() method which
+ * needs a previous loading of the classification model with the Load() method.
+ *
+ * \sa MachineLearningModelFactory
+ * \sa LibSVMMachineLearningModel
+ * \sa SVMMachineLearningModel
+ * \sa BoostMachineLearningModel
+ * \sa KNearestNeighborsMachineLearningModel
+ * \sa DecisionTreeMachineLearningModel
+ * \sa RandomForestsMachineLearningModel
+ * \sa GradientBoostedTreeMachineLearningModel
+ * \sa NormalBayesMachineLearningModel
+ * \sa NeuralNetworkMachineLearningModel
+ * \sa ImageClassificationFilter
+ *
+ */
 template <class TInputValue, class TTargetValue>
 class ITK_EXPORT MachineLearningModel
   : public itk::Object
@@ -54,29 +88,41 @@ public:
 
   /** Predict values using the model */
   virtual TargetSampleType Predict(const InputSampleType& input) const = 0;
+  
+  /** Classify all samples in InputListSample and fill TargetListSample with the associated label */
   void PredictAll();
 
+  /**\name Classification model file manipulation */
+  //@{
   /** Save the model to file */
   virtual void Save(const std::string & filename, const std::string & name="") = 0;
 
   /** Load the model from file */
   virtual void Load(const std::string & filename, const std::string & name="") = 0;
+  //@}
 
-  /** Determine the file type. Returns true if this ImageIO can read the
-   * file specified. */
+  /**\name Classification model file compatibility tests */
+  //@{
+  /** Is the input model file readable and compatible with the corresponding classifier ? */
   virtual bool CanReadFile(const std::string &) = 0;
 
-  /** Determine the file type. Returns true if this ImageIO can read the
-   * file specified. */
+  /** Is the input model file writable and compatible with the corresponding classifier ? */
   virtual bool CanWriteFile(const std::string &)  = 0;
+  //@}
 
-  /** Input accessors */
+  /**\name Input list of samples accessors */
+  //@{
   itkSetObjectMacro(InputListSample,InputListSampleType);
   itkGetObjectMacro(InputListSample,InputListSampleType);
+  //@}
 
-  /** Target accessors */
+  /**\name Classification output accessors */
+  //@{
+  /** Set the target labels (to be used before training) */
   itkSetObjectMacro(TargetListSample,TargetListSampleType);
+  /** Get the target labels (to be used after PredictAll) */
   itkGetObjectMacro(TargetListSample,TargetListSampleType);
+  //@}
 
 protected:
   /** Constructor */