Package org.opencv.ml
Class SVMSGD
- java.lang.Object
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- org.opencv.core.Algorithm
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- org.opencv.ml.StatModel
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- org.opencv.ml.SVMSGD
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public class SVMSGD extends StatModel
*************************************************************************************\ Stochastic Gradient Descent SVM Classifier * \***************************************************************************************
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Field Summary
Fields Modifier and Type Field Description static int
ASGD
static int
HARD_MARGIN
static int
SGD
static int
SOFT_MARGIN
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Fields inherited from class org.opencv.ml.StatModel
COMPRESSED_INPUT, PREPROCESSED_INPUT, RAW_OUTPUT, UPDATE_MODEL
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Constructor Summary
Constructors Modifier Constructor Description protected
SVMSGD(long addr)
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method Description static SVMSGD
__fromPtr__(long addr)
static SVMSGD
create()
Creates empty model.protected void
finalize()
float
getInitialStepSize()
SEE: setInitialStepSizefloat
getMarginRegularization()
SEE: setMarginRegularizationint
getMarginType()
SEE: setMarginTypefloat
getShift()
float
getStepDecreasingPower()
SEE: setStepDecreasingPowerint
getSvmsgdType()
SEE: setSvmsgdTypeTermCriteria
getTermCriteria()
SEE: setTermCriteriaMat
getWeights()
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.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.void
setInitialStepSize(float InitialStepSize)
getInitialStepSize SEE: getInitialStepSizevoid
setMarginRegularization(float marginRegularization)
getMarginRegularization SEE: getMarginRegularizationvoid
setMarginType(int marginType)
getMarginType SEE: getMarginTypevoid
setOptimalParameters()
Function sets optimal parameters values for chosen SVM SGD model.void
setOptimalParameters(int svmsgdType)
Function sets optimal parameters values for chosen SVM SGD model.void
setOptimalParameters(int svmsgdType, int marginType)
Function sets optimal parameters values for chosen SVM SGD model.void
setStepDecreasingPower(float stepDecreasingPower)
getStepDecreasingPower SEE: getStepDecreasingPowervoid
setSvmsgdType(int svmsgdType)
getSvmsgdType SEE: getSvmsgdTypevoid
setTermCriteria(TermCriteria val)
getTermCriteria SEE: getTermCriteria-
Methods inherited from class org.opencv.ml.StatModel
calcError, empty, getVarCount, isClassifier, isTrained, predict, predict, predict, train, train, train
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Methods inherited from class org.opencv.core.Algorithm
clear, getDefaultName, getNativeObjAddr, save
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Field Detail
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SOFT_MARGIN
public static final int SOFT_MARGIN
- See Also:
- Constant Field Values
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HARD_MARGIN
public static final int HARD_MARGIN
- See Also:
- Constant Field Values
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SGD
public static final int SGD
- See Also:
- Constant Field Values
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ASGD
public static final int ASGD
- See Also:
- Constant Field Values
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Method Detail
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__fromPtr__
public static SVMSGD __fromPtr__(long addr)
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getWeights
public Mat getWeights()
- Returns:
- the weights of the trained model (decision function f(x) = weights * x + shift).
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getShift
public float getShift()
- Returns:
- the shift of the trained model (decision function f(x) = weights * x + shift).
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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
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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 SVMSGDnodeName
- name of node containing the classifier- Returns:
- automatically generated
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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
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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.
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setOptimalParameters
public void setOptimalParameters(int svmsgdType)
Function sets optimal parameters values for chosen SVM SGD model.- Parameters:
svmsgdType
- is the type of SVMSGD classifier.
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setOptimalParameters
public void setOptimalParameters()
Function sets optimal parameters values for chosen SVM SGD model.
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getSvmsgdType
public int getSvmsgdType()
SEE: setSvmsgdType- Returns:
- automatically generated
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setSvmsgdType
public void setSvmsgdType(int svmsgdType)
getSvmsgdType SEE: getSvmsgdType- Parameters:
svmsgdType
- automatically generated
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getMarginType
public int getMarginType()
SEE: setMarginType- Returns:
- automatically generated
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setMarginType
public void setMarginType(int marginType)
getMarginType SEE: getMarginType- Parameters:
marginType
- automatically generated
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getMarginRegularization
public float getMarginRegularization()
SEE: setMarginRegularization- Returns:
- automatically generated
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setMarginRegularization
public void setMarginRegularization(float marginRegularization)
getMarginRegularization SEE: getMarginRegularization- Parameters:
marginRegularization
- automatically generated
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getInitialStepSize
public float getInitialStepSize()
SEE: setInitialStepSize- Returns:
- automatically generated
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setInitialStepSize
public void setInitialStepSize(float InitialStepSize)
getInitialStepSize SEE: getInitialStepSize- Parameters:
InitialStepSize
- automatically generated
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getStepDecreasingPower
public float getStepDecreasingPower()
SEE: setStepDecreasingPower- Returns:
- automatically generated
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setStepDecreasingPower
public void setStepDecreasingPower(float stepDecreasingPower)
getStepDecreasingPower SEE: getStepDecreasingPower- Parameters:
stepDecreasingPower
- automatically generated
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getTermCriteria
public TermCriteria getTermCriteria()
SEE: setTermCriteria- Returns:
- automatically generated
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setTermCriteria
public void setTermCriteria(TermCriteria val)
getTermCriteria SEE: getTermCriteria- Parameters:
val
- automatically generated
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