Package org.opencv.ml

Class SVMSGD

java.lang.Object
org.opencv.core.Algorithm
org.opencv.ml.StatModel
org.opencv.ml.SVMSGD
public class SVMSGD extends StatModel
*************************************************************************************\ Stochastic Gradient Descent SVM Classifier * \***************************************************************************************

  • Field Details

  • Method Details

    • __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(String filepath, 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(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