Package org.opencv.ml

Class NormalBayesClassifier


  • public class NormalBayesClassifier
    extends StatModel
    Bayes classifier for normally distributed data. SEE: REF: ml_intro_bayes
    • Constructor Detail

      • NormalBayesClassifier

        protected NormalBayesClassifier​(long addr)
    • Method Detail

      • create

        public static NormalBayesClassifier create()
        Creates empty model Use StatModel::train to train the model after creation.
        Returns:
        automatically generated
      • load

        public static NormalBayesClassifier load​(java.lang.String filepath,
                                                 java.lang.String 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
        Parameters:
        filepath - path to serialized NormalBayesClassifier
        nodeName - name of node containing the classifier
        Returns:
        automatically generated
      • load

        public static NormalBayesClassifier load​(java.lang.String filepath)
        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
        Parameters:
        filepath - path to serialized NormalBayesClassifier
        Returns:
        automatically generated
      • predictProb

        public float predictProb​(Mat inputs,
                                 Mat outputs,
                                 Mat outputProbs,
                                 int 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.
        Parameters:
        inputs - automatically generated
        outputs - automatically generated
        outputProbs - automatically generated
        flags - automatically generated
        Returns:
        automatically generated
      • predictProb

        public float predictProb​(Mat inputs,
                                 Mat outputs,
                                 Mat outputProbs)
        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.
        Parameters:
        inputs - automatically generated
        outputs - automatically generated
        outputProbs - automatically generated
        Returns:
        automatically generated
      • finalize

        protected void finalize()
                         throws java.lang.Throwable
        Overrides:
        finalize in class StatModel
        Throws:
        java.lang.Throwable