OpenCV reference manual (C++ part only for now) is now produced directly from RST, not from TeX.

modules/ml/doc/normal_bayes_classifier.rst

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+Normal Bayes Classifier
+=======================
+
+.. highlight:: cpp
+
+
+This is a simple classification model assuming that feature vectors from each class are normally distributed (though, not necessarily independently distributed), so the whole data distribution function is assumed to be a Gaussian mixture, one component per  class. Using the training data the algorithm estimates mean vectors and covariance matrices for every class, and then it uses them for prediction.
+
+**[Fukunaga90] K. Fukunaga. Introduction to Statistical Pattern Recognition. second ed., New York: Academic Press, 1990.**
+
+.. index:: CvNormalBayesClassifier
+
+.. _CvNormalBayesClassifier:
+
+CvNormalBayesClassifier
+-----------------------
+
+`id=0.110421013491 Comments from the Wiki <http://opencv.willowgarage.com/wiki/documentation/cpp/ml/CvNormalBayesClassifier>`__
+
+.. ctype:: CvNormalBayesClassifier
+
+
+
+Bayes classifier for normally distributed data.
+
+
+
+
+::
+
+
+    
+    class CvNormalBayesClassifier : public CvStatModel
+    {
+    public:
+        CvNormalBayesClassifier();
+        virtual ~CvNormalBayesClassifier();
+    
+        CvNormalBayesClassifier( const CvMat* _train_data, const CvMat* _responses,
+            const CvMat* _var_idx=0, const CvMat* _sample_idx=0 );
+    
+        virtual bool train( const CvMat* _train_data, const CvMat* _responses,
+            const CvMat* _var_idx = 0, const CvMat* _sample_idx=0, bool update=false );
+    
+        virtual float predict( const CvMat* _samples, CvMat* results=0 ) const;
+        virtual void clear();
+    
+        virtual void save( const char* filename, const char* name=0 );
+        virtual void load( const char* filename, const char* name=0 );
+    
+        virtual void write( CvFileStorage* storage, const char* name );
+        virtual void read( CvFileStorage* storage, CvFileNode* node );
+    protected:
+        ...
+    };
+    
+
+..
+
+
+.. index:: CvNormalBayesClassifier::train
+
+.. _CvNormalBayesClassifier::train:
+
+CvNormalBayesClassifier::train
+------------------------------
+
+`id=0.746566750452 Comments from the Wiki <http://opencv.willowgarage.com/wiki/documentation/cpp/ml/CvNormalBayesClassifier%3A%3Atrain>`__
+
+
+
+
+.. cfunction:: bool CvNormalBayesClassifier::train(  const CvMat* _train_data,  const CvMat* _responses,                 const CvMat* _var_idx =0,  const CvMat* _sample_idx=0,  bool update=false )
+
+    Trains the model.
+
+
+
+The method trains the Normal Bayes classifier. It follows the conventions of the generic 
+``train``
+"method" with the following limitations: only CV
+_
+ROW
+_
+SAMPLE data layout is supported; the input variables are all ordered; the output variable is categorical (i.e. elements of 
+``_responses``
+must be integer numbers, though the vector may have 
+``CV_32FC1``
+type), and missing measurements are not supported.
+
+In addition, there is an 
+``update``
+flag that identifies whether the model should be trained from scratch (
+``update=false``
+) or should be updated using the new training data (
+``update=true``
+).
+
+
+.. index:: CvNormalBayesClassifier::predict
+
+.. _CvNormalBayesClassifier::predict:
+
+CvNormalBayesClassifier::predict
+--------------------------------
+
+`id=0.821415185096 Comments from the Wiki <http://opencv.willowgarage.com/wiki/documentation/cpp/ml/CvNormalBayesClassifier%3A%3Apredict>`__
+
+
+
+
+.. cfunction:: float CvNormalBayesClassifier::predict(  const CvMat* samples,  CvMat* results=0 ) const
+
+    Predicts the response for sample(s)
+
+
+
+The method 
+``predict``
+estimates the most probable classes for the input vectors. The input vectors (one or more) are stored as rows of the matrix 
+``samples``
+. In the case of multiple input vectors, there should be one output vector 
+``results``
+. The predicted class for a single input vector is returned by the method.
+