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OpenCV 2.4.3.1
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## org.opencv.ml
Class CvNormalBayesClassifier

    java.lang.Object
      org.opencv.ml.CvStatModel
          org.opencv.ml.CvNormalBayesClassifier

    public class CvNormalBayesClassifier

extends CvStatModel

Bayes classifier for normally distributed data.

See Also:
  org.opencv.ml.CvNormalBayesClassifier : public CvStatModel

Field Summary

Fields inherited from class org.opencv.ml.CvStatModel
`nativeObj`

Constructor Summary
`` | `CvNormalBayesClassifier()` Default and training constructors.
`protected` | `CvNormalBayesClassifier(long addr)`
`` | `CvNormalBayesClassifier(Mat trainData, Mat responses)` Default and training constructors.
`` | `CvNormalBayesClassifier(Mat trainData, Mat responses, Mat varIdx, Mat sampleIdx)` Default and training constructors.

Method Summary
`void` | `clear()`
`protected void` | `finalize()`
`float` | `predict(Mat samples)` Predicts the response for sample(s).
`float` | `predict(Mat samples, Mat results)` Predicts the response for sample(s).
`boolean` | `train(Mat trainData, Mat responses)` Trains the model.
`boolean` | `train(Mat trainData, Mat responses, Mat varIdx, Mat sampleIdx, boolean update)` Trains the model.

Methods inherited from class org.opencv.ml.CvStatModel
`load, load, save, save`

Methods inherited from class java.lang.Object
`clone, equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

Constructor Detail

### CvNormalBayesClassifier

    public CvNormalBayesClassifier()

  Default and training constructors.

  The constructors follow conventions of "CvStatModel.CvStatModel". See "CvStatModel.train" for parameters descriptions.

  See Also:
    org.opencv.ml.CvNormalBayesClassifier.CvNormalBayesClassifier

### CvNormalBayesClassifier

    protected CvNormalBayesClassifier(long addr)

### CvNormalBayesClassifier

    public CvNormalBayesClassifier(Mat trainData,
                                   Mat responses)

  Default and training constructors.

  The constructors follow conventions of "CvStatModel.CvStatModel". See "CvStatModel.train" for parameters descriptions.

  Parameters:
    `trainData` - a trainData
    `responses` - a responses
  See Also:
    org.opencv.ml.CvNormalBayesClassifier.CvNormalBayesClassifier

### CvNormalBayesClassifier

    public CvNormalBayesClassifier(Mat trainData,
                                   Mat responses,
                                   Mat varIdx,
                                   Mat sampleIdx)

  Default and training constructors.

  The constructors follow conventions of "CvStatModel.CvStatModel". See "CvStatModel.train" for parameters descriptions.

  Parameters:
    `trainData` - a trainData
    `responses` - a responses
    `varIdx` - a varIdx
    `sampleIdx` - a sampleIdx
  See Also:
    org.opencv.ml.CvNormalBayesClassifier.CvNormalBayesClassifier

Method Detail

### clear

    public void clear()

### finalize

    protected void finalize()
                     throws java.lang.Throwable

  Overrides:
    `finalize` in class `CvStatModel`
  Throws:
    `java.lang.Throwable`

### predict

    public float predict(Mat samples)

  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 `samples`. In 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.

  The function is parallelized with the TBB library.

  Parameters:
    `samples` - a samples
  See Also:
    org.opencv.ml.CvNormalBayesClassifier.predict

### predict

    public float predict(Mat samples,
                         Mat results)

  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 `samples`. In 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.

  The function is parallelized with the TBB library.

  Parameters:
    `samples` - a samples
    `results` - a results
  See Also:
    org.opencv.ml.CvNormalBayesClassifier.predict

### train

    public boolean train(Mat trainData,
                         Mat responses)

  Trains the model.

  The method trains the Normal Bayes classifier. It follows the conventions of the generic "CvStatModel.train" approach with the following limitations:

  - Only `CV_ROW_SAMPLE` data layout is supported.
  - Input variables are all ordered.
  - Output variable is categorical, which means that elements of `responses` must be integer numbers, though the vector may have the `CV_32FC1` type.
  - Missing measurements are not supported.

  Parameters:
    `trainData` - a trainData
    `responses` - a responses
  See Also:
    org.opencv.ml.CvNormalBayesClassifier.train

### train

    public boolean train(Mat trainData,
                         Mat responses,
                         Mat varIdx,
                         Mat sampleIdx,
                         boolean update)

  Trains the model.

  The method trains the Normal Bayes classifier. It follows the conventions of the generic "CvStatModel.train" approach with the following limitations:

  - Only `CV_ROW_SAMPLE` data layout is supported.
  - Input variables are all ordered.
  - Output variable is categorical, which means that elements of `responses` must be integer numbers, though the vector may have the `CV_32FC1` type.
  - Missing measurements are not supported.

  Parameters:
    `trainData` - a trainData
    `responses` - a responses
    `varIdx` - a varIdx
    `sampleIdx` - a sampleIdx
    `update` - Identifies whether the model should be trained from scratch (`update=false`) or should be updated using the new training data (`update=true`).
  See Also:
    org.opencv.ml.CvNormalBayesClassifier.train

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