|
||||||||||
PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
java.lang.Objectweka.classifiers.Classifier
weka.classifiers.functions.SMOreg
public class SMOreg
Implements Alex Smola and Bernhard Scholkopf's sequential minimal optimization algorithm for training a support vector regression model. This implementation globally replaces all missing values and transforms nominal attributes into binary ones. It also normalizes all attributes by default. (Note that the coefficients in the output are based on the normalized/standardized data, not the original data.)
For more information on the SMO algorithm, see
Alex J. Smola, Bernhard Schoelkopf: A Tutorial on Support Vector Regression. In NeuroCOLT2 Technical Report Series, 1998.
S.K. Shevade, S.S. Keerthi, C. Bhattacharyya, K.R.K. Murthy (1999). Improvements to SMO Algorithm for SVM Regression. Control Division Dept of Mechanical and Production Engineering, National University of Singapore.
@incollection{Smola1998, author = {Alex J. Smola and Bernhard Schoelkopf}, booktitle = {NeuroCOLT2 Technical Report Series}, note = {NC2-TR-1998-030}, title = {A Tutorial on Support Vector Regression}, year = {1998} } @techreport{Shevade1999, address = {Control Division Dept of Mechanical and Production Engineering, National University of Singapore}, author = {S.K. Shevade and S.S. Keerthi and C. Bhattacharyya and K.R.K. Murthy}, institution = {National University of Singapore}, note = {Technical Report CD-99-16}, title = {Improvements to SMO Algorithm for SVM Regression}, year = {1999} }Valid options are:
-D If set, classifier is run in debug mode and may output additional info to the console
-no-checks Turns off all checks - use with caution! Turning them off assumes that data is purely numeric, doesn't contain any missing values, and has a nominal class. Turning them off also means that no header information will be stored if the machine is linear. Finally, it also assumes that no instance has a weight equal to 0. (default: checks on)
-S <double> The amount up to which deviations are tolerated (epsilon). (default 1e-3)
-C <double> The complexity constant C. (default 1)
-N Whether to 0=normalize/1=standardize/2=neither. (default 0=normalize)
-T <double> The tolerance parameter. (default 1.0e-3)
-P <double> The epsilon for round-off error. (default 1.0e-12)
-K <classname and parameters> The Kernel to use. (default: weka.classifiers.functions.supportVector.PolyKernel)
Options specific to kernel weka.classifiers.functions.supportVector.PolyKernel:
-D Enables debugging output (if available) to be printed. (default: off)
-no-checks Turns off all checks - use with caution! (default: checks on)
-C <num> The size of the cache (a prime number), 0 for full cache and -1 to turn it off. (default: 250007)
-E <num> The Exponent to use. (default: 1.0)
-L Use lower-order terms. (default: no)
Field Summary | |
---|---|
static int |
FILTER_NONE
no filtering |
static int |
FILTER_NORMALIZE
normalize data |
static int |
FILTER_STANDARDIZE
standardize data |
static Tag[] |
TAGS_FILTER
The filter to apply to the training data |
Constructor Summary | |
---|---|
SMOreg()
|
Method Summary | |
---|---|
void |
buildClassifier(Instances insts)
Method for building the classifier. |
java.lang.String |
checksTurnedOffTipText()
Returns the tip text for this property |
double |
classifyInstance(Instance inst)
Classifies a given instance. |
java.lang.String |
cTipText()
Returns the tip text for this property |
java.lang.String |
epsilonTipText()
Returns the tip text for this property |
java.lang.String |
epsTipText()
Returns the tip text for this property |
java.lang.String |
filterTypeTipText()
Returns the tip text for this property |
double |
getC()
Get the value of C. |
Capabilities |
getCapabilities()
Returns default capabilities of the classifier. |
boolean |
getChecksTurnedOff()
Returns whether the checks are turned off or not. |
double |
getEps()
Get the value of eps. |
double |
getEpsilon()
Get the value of epsilon. |
SelectedTag |
getFilterType()
Gets how the training data will be transformed. |
Kernel |
getKernel()
Gets the kernel to use. |
java.lang.String[] |
getOptions()
Gets the current settings of the classifier. |
TechnicalInformation |
getTechnicalInformation()
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on. |
double |
getToleranceParameter()
Get the value of tolerance parameter. |
java.lang.String |
globalInfo()
Returns a string describing classifier |
java.lang.String |
kernelTipText()
Returns the tip text for this property |
java.util.Enumeration |
listOptions()
Returns an enumeration describing the available options. |
static void |
main(java.lang.String[] argv)
Main method for testing this class. |
void |
setC(double v)
Set the value of C. |
void |
setChecksTurnedOff(boolean value)
Disables or enables the checks (which could be time-consuming). |
void |
setEps(double v)
Set the value of eps. |
void |
setEpsilon(double v)
Set the value of epsilon. |
void |
setFilterType(SelectedTag newType)
Sets how the training data will be transformed. |
void |
setKernel(Kernel value)
Sets the kernel to use. |
void |
setOptions(java.lang.String[] options)
Parses a given list of options. |
void |
setToleranceParameter(double v)
Set the value of tolerance parameter. |
java.lang.String |
toleranceParameterTipText()
Returns the tip text for this property |
java.lang.String |
toString()
Prints out the classifier. |
void |
turnChecksOff()
Turns off checks for missing values, etc. |
void |
turnChecksOn()
Turns on checks for missing values, etc. |
Methods inherited from class weka.classifiers.Classifier |
---|
debugTipText, distributionForInstance, forName, getDebug, makeCopies, makeCopy, setDebug |
Methods inherited from class java.lang.Object |
---|
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Field Detail |
---|
public static final int FILTER_NORMALIZE
public static final int FILTER_STANDARDIZE
public static final int FILTER_NONE
public static final Tag[] TAGS_FILTER
Constructor Detail |
---|
public SMOreg()
Method Detail |
---|
public java.lang.String globalInfo()
public TechnicalInformation getTechnicalInformation()
getTechnicalInformation
in interface TechnicalInformationHandler
public Capabilities getCapabilities()
getCapabilities
in interface CapabilitiesHandler
getCapabilities
in class Classifier
Capabilities
public void buildClassifier(Instances insts) throws java.lang.Exception
buildClassifier
in class Classifier
insts
- the set of training instances
java.lang.Exception
- if the classifier can't be built successfullypublic double classifyInstance(Instance inst) throws java.lang.Exception
classifyInstance
in class Classifier
inst
- the instance to be classified
java.lang.Exception
- if instance could not be classified
successfullypublic java.util.Enumeration listOptions()
listOptions
in interface OptionHandler
listOptions
in class Classifier
public void setOptions(java.lang.String[] options) throws java.lang.Exception
setOptions
in interface OptionHandler
setOptions
in class Classifier
options
- the list of options as an array of strings
java.lang.Exception
- if an option is not supportedpublic java.lang.String[] getOptions()
getOptions
in interface OptionHandler
getOptions
in class Classifier
public void setChecksTurnedOff(boolean value)
value
- if true turns off all checkspublic boolean getChecksTurnedOff()
public java.lang.String checksTurnedOffTipText()
public java.lang.String kernelTipText()
public Kernel getKernel()
public void setKernel(Kernel value)
value
- the kernelpublic java.lang.String filterTypeTipText()
public SelectedTag getFilterType()
public void setFilterType(SelectedTag newType)
newType
- the new filtering modepublic java.lang.String cTipText()
public double getC()
public void setC(double v)
v
- Value to assign to C.public java.lang.String toleranceParameterTipText()
public double getToleranceParameter()
public void setToleranceParameter(double v)
v
- Value to assign to tolerance parameter.public java.lang.String epsTipText()
public double getEps()
public void setEps(double v)
v
- Value to assign to epsilon.public java.lang.String epsilonTipText()
public double getEpsilon()
public void setEpsilon(double v)
v
- Value to assign to epsilon.public void turnChecksOff()
public void turnChecksOn()
public java.lang.String toString()
toString
in class java.lang.Object
public static void main(java.lang.String[] argv)
argv
- the commandline options
|
||||||||||
PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |