public class PLSClassifier
extends weka.classifiers.RandomizableClassifier
implements weka.core.WeightedInstancesHandler
-filter <filter specification> The PLS filter to use. Full classname of filter to include, followed by scheme options. (default: weka.filters.supervised.attribute.PLSFilter)
-D If set, classifier is run in debug mode and may output additional info to the console
Options specific to filter weka.filters.supervised.attribute.PLSFilter ('-filter'):
-D Turns on output of debugging information.
-C <num> The number of components to compute. (default: 20)
-U Updates the class attribute as well. (default: off)
-M Turns replacing of missing values on. (default: off)
-A <SIMPLS|PLS1> The algorithm to use. (default: PLS1)
-P <none|center|standardize> The type of preprocessing that is applied to the data. (default: center)
| Constructor and Description |
|---|
PLSClassifier() |
| Modifier and Type | Method and Description |
|---|---|
void |
buildClassifier(weka.core.Instances data)
builds the classifier
|
double |
classifyInstance(weka.core.Instance instance)
Classifies the given test instance.
|
String |
filterTipText()
Returns the tip text for this property
|
weka.core.Capabilities |
getCapabilities()
Returns default capabilities of the classifier.
|
weka.filters.Filter |
getFilter()
Get the PLS filter.
|
String[] |
getOptions()
returns the options of the current setup
|
String |
getRevision()
Returns the revision string.
|
String |
globalInfo()
Returns a string describing classifier
|
Enumeration<weka.core.Option> |
listOptions()
Gets an enumeration describing the available options.
|
static void |
main(String[] args)
Main method for running this classifier from commandline.
|
void |
setFilter(weka.filters.Filter value)
Set the PLS filter (only used for setup).
|
void |
setOptions(String[] options)
Parses the options for this object.
|
String |
toString()
returns a string representation of the classifier
|
batchSizeTipText, debugTipText, distributionForInstance, distributionsForInstances, doNotCheckCapabilitiesTipText, forName, getBatchSize, getDebug, getDoNotCheckCapabilities, getNumDecimalPlaces, implementsMoreEfficientBatchPrediction, makeCopies, makeCopy, numDecimalPlacesTipText, postExecution, preExecution, run, runClassifier, setBatchSize, setDebug, setDoNotCheckCapabilities, setNumDecimalPlacespublic String globalInfo()
public Enumeration<weka.core.Option> listOptions()
listOptions in interface weka.core.OptionHandlerlistOptions in class weka.classifiers.RandomizableClassifierpublic String[] getOptions()
getOptions in interface weka.core.OptionHandlergetOptions in class weka.classifiers.RandomizableClassifierpublic void setOptions(String[] options) throws Exception
-filter <filter specification> The PLS filter to use. Full classname of filter to include, followed by scheme options. (default: weka.filters.supervised.attribute.PLSFilter)
-D If set, classifier is run in debug mode and may output additional info to the console
Options specific to filter weka.filters.supervised.attribute.PLSFilter ('-filter'):
-D Turns on output of debugging information.
-C <num> The number of components to compute. (default: 20)
-U Updates the class attribute as well. (default: off)
-M Turns replacing of missing values on. (default: off)
-A <SIMPLS|PLS1> The algorithm to use. (default: PLS1)
-P <none|center|standardize> The type of preprocessing that is applied to the data. (default: center)
setOptions in interface weka.core.OptionHandlersetOptions in class weka.classifiers.RandomizableClassifieroptions - the options to useException - if setting of options failspublic String filterTipText()
public void setFilter(weka.filters.Filter value)
throws Exception
value - the kernel filter.Exception - if not PLSFilterpublic weka.filters.Filter getFilter()
public weka.core.Capabilities getCapabilities()
getCapabilities in interface weka.classifiers.ClassifiergetCapabilities in interface weka.core.CapabilitiesHandlergetCapabilities in class weka.classifiers.AbstractClassifierpublic void buildClassifier(weka.core.Instances data)
throws Exception
buildClassifier in interface weka.classifiers.Classifierdata - the training instancesException - if something goes wrongpublic double classifyInstance(weka.core.Instance instance)
throws Exception
classifyInstance in interface weka.classifiers.ClassifierclassifyInstance in class weka.classifiers.AbstractClassifierinstance - the instance to be classifiedException - if an error occurred during the predictionpublic String toString()
public String getRevision()
getRevision in interface weka.core.RevisionHandlergetRevision in class weka.classifiers.AbstractClassifierpublic static void main(String[] args)
args - the optionsCopyright © 2018 University of Waikato, Hamilton, NZ. All Rights Reserved.