Package org.opencv.ml

Class SVMSGD


  • public class SVMSGD
    extends StatModel
    *************************************************************************************\ Stochastic Gradient Descent SVM Classifier * \***************************************************************************************
    • Constructor Detail

      • SVMSGD

        protected SVMSGD​(long addr)
    • Method Detail

      • __fromPtr__

        public static SVMSGD __fromPtr__​(long addr)
      • getWeights

        public Mat getWeights()
        Returns:
        the weights of the trained model (decision function f(x) = weights * x + shift).
      • getShift

        public float getShift()
        Returns:
        the shift of the trained model (decision function f(x) = weights * x + shift).
      • create

        public static SVMSGD create()
        Creates empty model. Use StatModel::train to train the model. Since %SVMSGD has several parameters, you may want to find the best parameters for your problem or use setOptimalParameters() to set some default parameters.
        Returns:
        automatically generated
      • load

        public static SVMSGD load​(java.lang.String filepath,
                                  java.lang.String nodeName)
        Loads and creates a serialized SVMSGD from a file Use SVMSGD::save to serialize and store an SVMSGD to disk. Load the SVMSGD 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 SVMSGD
        nodeName - name of node containing the classifier
        Returns:
        automatically generated
      • load

        public static SVMSGD load​(java.lang.String filepath)
        Loads and creates a serialized SVMSGD from a file Use SVMSGD::save to serialize and store an SVMSGD to disk. Load the SVMSGD 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 SVMSGD
        Returns:
        automatically generated
      • setOptimalParameters

        public void setOptimalParameters​(int svmsgdType,
                                         int marginType)
        Function sets optimal parameters values for chosen SVM SGD model.
        Parameters:
        svmsgdType - is the type of SVMSGD classifier.
        marginType - is the type of margin constraint.
      • setOptimalParameters

        public void setOptimalParameters​(int svmsgdType)
        Function sets optimal parameters values for chosen SVM SGD model.
        Parameters:
        svmsgdType - is the type of SVMSGD classifier.
      • setOptimalParameters

        public void setOptimalParameters()
        Function sets optimal parameters values for chosen SVM SGD model.
      • getSvmsgdType

        public int getSvmsgdType()
        SEE: setSvmsgdType
        Returns:
        automatically generated
      • setSvmsgdType

        public void setSvmsgdType​(int svmsgdType)
        getSvmsgdType SEE: getSvmsgdType
        Parameters:
        svmsgdType - automatically generated
      • getMarginType

        public int getMarginType()
        SEE: setMarginType
        Returns:
        automatically generated
      • setMarginType

        public void setMarginType​(int marginType)
        getMarginType SEE: getMarginType
        Parameters:
        marginType - automatically generated
      • getMarginRegularization

        public float getMarginRegularization()
        SEE: setMarginRegularization
        Returns:
        automatically generated
      • setMarginRegularization

        public void setMarginRegularization​(float marginRegularization)
        getMarginRegularization SEE: getMarginRegularization
        Parameters:
        marginRegularization - automatically generated
      • getInitialStepSize

        public float getInitialStepSize()
        SEE: setInitialStepSize
        Returns:
        automatically generated
      • setInitialStepSize

        public void setInitialStepSize​(float InitialStepSize)
        getInitialStepSize SEE: getInitialStepSize
        Parameters:
        InitialStepSize - automatically generated
      • getStepDecreasingPower

        public float getStepDecreasingPower()
        SEE: setStepDecreasingPower
        Returns:
        automatically generated
      • setStepDecreasingPower

        public void setStepDecreasingPower​(float stepDecreasingPower)
        getStepDecreasingPower SEE: getStepDecreasingPower
        Parameters:
        stepDecreasingPower - automatically generated
      • getTermCriteria

        public TermCriteria getTermCriteria()
        SEE: setTermCriteria
        Returns:
        automatically generated
      • setTermCriteria

        public void setTermCriteria​(TermCriteria val)
        getTermCriteria SEE: getTermCriteria
        Parameters:
        val - automatically generated
      • finalize

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