content: //
  // This file is auto-generated. Please don't modify it!
  //
  package org.opencv.ml;
  
  import org.opencv.core.Mat;
  import org.opencv.ml.NormalBayesClassifier;
  import org.opencv.ml.StatModel;
  
  // C++: class NormalBayesClassifier
  /**
   * Bayes classifier for normally distributed data.
   *
   * SEE: REF: ml_intro_bayes
   */
  public class NormalBayesClassifier extends StatModel {
  
      protected NormalBayesClassifier(long addr) { super(addr); }
  
      // internal usage only
      public static NormalBayesClassifier __fromPtr__(long addr) { return new NormalBayesClassifier(addr); }
  
      //
      // C++: static Ptr_NormalBayesClassifier cv::ml::NormalBayesClassifier::create()
      //
  
      /**
       * Creates empty model
       * Use StatModel::train to train the model after creation.
       * @return automatically generated
       */
      public static NormalBayesClassifier create() {
          return NormalBayesClassifier.__fromPtr__(create_0());
      }
  
  
      //
      // C++: static Ptr_NormalBayesClassifier cv::ml::NormalBayesClassifier::load(String filepath, String nodeName = String())
      //
  
      /**
       * Loads and creates a serialized NormalBayesClassifier from a file
       *
       * Use NormalBayesClassifier::save to serialize and store an NormalBayesClassifier to disk.
       * Load the NormalBayesClassifier from this file again, by calling this function with the path to the file.
       * Optionally specify the node for the file containing the classifier
       *
       * @param filepath path to serialized NormalBayesClassifier
       * @param nodeName name of node containing the classifier
       * @return automatically generated
       */
      public static NormalBayesClassifier load(String filepath, String nodeName) {
          return NormalBayesClassifier.__fromPtr__(load_0(filepath, nodeName));
      }
  
      /**
       * Loads and creates a serialized NormalBayesClassifier from a file
       *
       * Use NormalBayesClassifier::save to serialize and store an NormalBayesClassifier to disk.
       * Load the NormalBayesClassifier from this file again, by calling this function with the path to the file.
       * Optionally specify the node for the file containing the classifier
       *
       * @param filepath path to serialized NormalBayesClassifier
       * @return automatically generated
       */
      public static NormalBayesClassifier load(String filepath) {
          return NormalBayesClassifier.__fromPtr__(load_1(filepath));
      }
  
  
      //
      // C++:  float cv::ml::NormalBayesClassifier::predictProb(Mat inputs, Mat& outputs, Mat& outputProbs, int flags = 0)
      //
  
      /**
       * Predicts the response for sample(s).
       *
       *     The method estimates the most probable classes for input vectors. Input vectors (one or more)
       *     are stored as rows of the matrix inputs. In case of multiple input vectors, there should be one
       *     output vector outputs. The predicted class for a single input vector is returned by the method.
       *     The vector outputProbs contains the output probabilities corresponding to each element of
       *     result.
       * @param inputs automatically generated
       * @param outputs automatically generated
       * @param outputProbs automatically generated
       * @param flags automatically generated
       * @return automatically generated
       */
      public float predictProb(Mat inputs, Mat outputs, Mat outputProbs, int flags) {
          return predictProb_0(nativeObj, inputs.nativeObj, outputs.nativeObj, outputProbs.nativeObj, flags);
      }
  
      /**
       * Predicts the response for sample(s).
       *
       *     The method estimates the most probable classes for input vectors. Input vectors (one or more)
       *     are stored as rows of the matrix inputs. In case of multiple input vectors, there should be one
       *     output vector outputs. The predicted class for a single input vector is returned by the method.
       *     The vector outputProbs contains the output probabilities corresponding to each element of
       *     result.
       * @param inputs automatically generated
       * @param outputs automatically generated
       * @param outputProbs automatically generated
       * @return automatically generated
       */
      public float predictProb(Mat inputs, Mat outputs, Mat outputProbs) {
          return predictProb_1(nativeObj, inputs.nativeObj, outputs.nativeObj, outputProbs.nativeObj);
      }
  
  
      @Override
      protected void finalize() throws Throwable {
          delete(nativeObj);
      }
  
  
  
      // C++: static Ptr_NormalBayesClassifier cv::ml::NormalBayesClassifier::create()
      private static native long create_0();
  
      // C++: static Ptr_NormalBayesClassifier cv::ml::NormalBayesClassifier::load(String filepath, String nodeName = String())
      private static native long load_0(String filepath, String nodeName);
      private static native long load_1(String filepath);
  
      // C++:  float cv::ml::NormalBayesClassifier::predictProb(Mat inputs, Mat& outputs, Mat& outputProbs, int flags = 0)
      private static native float predictProb_0(long nativeObj, long inputs_nativeObj, long outputs_nativeObj, long outputProbs_nativeObj, int flags);
      private static native float predictProb_1(long nativeObj, long inputs_nativeObj, long outputs_nativeObj, long outputProbs_nativeObj);
  
      // native support for java finalize()
      private static native void delete(long nativeObj);
  
  }
  