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java.lang.Objectweka.classifiers.Classifier
weka.classifiers.functions.Winnow
public class Winnow
Implements Winnow and Balanced Winnow algorithms by Littlestone.
For more information, see
N. Littlestone (1988). Learning quickly when irrelevant attributes are abound: A new linear threshold algorithm. Machine Learning. 2:285-318.
N. Littlestone (1989). Mistake bounds and logarithmic linear-threshold learning algorithms. University of California, Santa Cruz.
Does classification for problems with nominal attributes (which it converts into binary attributes).
@article{Littlestone1988,
author = {N. Littlestone},
journal = {Machine Learning},
pages = {285-318},
title = {Learning quickly when irrelevant attributes are abound: A new linear threshold algorithm},
volume = {2},
year = {1988}
}
@techreport{Littlestone1989,
address = {University of California, Santa Cruz},
author = {N. Littlestone},
institution = {University of California},
note = {Technical Report UCSC-CRL-89-11},
title = {Mistake bounds and logarithmic linear-threshold learning algorithms},
year = {1989}
}
Valid options are:
-L Use the baLanced version (default false)
-I <int> The number of iterations to be performed. (default 1)
-A <double> Promotion coefficient alpha. (default 2.0)
-B <double> Demotion coefficient beta. (default 0.5)
-H <double> Prediction threshold. (default -1.0 == number of attributes)
-W <double> Starting weights. (default 2.0)
-S <int> Default random seed. (default 1)
| Constructor Summary | |
|---|---|
Winnow()
|
|
| Method Summary | |
|---|---|
java.lang.String |
alphaTipText()
Returns the tip text for this property |
java.lang.String |
balancedTipText()
Returns the tip text for this property |
java.lang.String |
betaTipText()
Returns the tip text for this property |
void |
buildClassifier(Instances insts)
Builds the classifier |
double |
classifyInstance(Instance inst)
Outputs the prediction for the given instance. |
java.lang.String |
defaultWeightTipText()
Returns the tip text for this property |
double |
getAlpha()
Get the value of Alpha. |
boolean |
getBalanced()
Get the value of Balanced. |
double |
getBeta()
Get the value of Beta. |
Capabilities |
getCapabilities()
Returns default capabilities of the classifier. |
double |
getDefaultWeight()
Get the value of defaultWeight. |
int |
getNumIterations()
Get the value of numIterations. |
java.lang.String[] |
getOptions()
Gets the current settings of the classifier. |
java.lang.String |
getRevision()
Returns the revision string. |
int |
getSeed()
Get the value of Seed. |
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 |
getThreshold()
Get the value of Threshold. |
java.lang.String |
globalInfo()
Returns a string describing classifier |
java.util.Enumeration |
listOptions()
Returns an enumeration describing the available options |
static void |
main(java.lang.String[] argv)
Main method. |
java.lang.String |
numIterationsTipText()
Returns the tip text for this property |
java.lang.String |
seedTipText()
Returns the tip text for this property |
void |
setAlpha(double a)
Set the value of Alpha. |
void |
setBalanced(boolean b)
Set the value of Balanced. |
void |
setBeta(double b)
Set the value of Beta. |
void |
setDefaultWeight(double w)
Set the value of defaultWeight. |
void |
setNumIterations(int v)
Set the value of numIterations. |
void |
setOptions(java.lang.String[] options)
Parses a given list of options. Valid options are: |
void |
setSeed(int v)
Set the value of Seed. |
void |
setThreshold(double t)
Set the value of Threshold. |
java.lang.String |
thresholdTipText()
Returns the tip text for this property |
java.lang.String |
toString()
Returns textual description of the classifier. |
void |
updateClassifier(Instance instance)
Updates the classifier with a new learning example |
| 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 |
| Constructor Detail |
|---|
public Winnow()
| Method Detail |
|---|
public java.lang.String globalInfo()
public TechnicalInformation getTechnicalInformation()
getTechnicalInformation in interface TechnicalInformationHandlerpublic java.util.Enumeration listOptions()
listOptions in interface OptionHandlerlistOptions in class Classifier
public void setOptions(java.lang.String[] options)
throws java.lang.Exception
-L Use the baLanced version (default false)
-I <int> The number of iterations to be performed. (default 1)
-A <double> Promotion coefficient alpha. (default 2.0)
-B <double> Demotion coefficient beta. (default 0.5)
-H <double> Prediction threshold. (default -1.0 == number of attributes)
-W <double> Starting weights. (default 2.0)
-S <int> Default random seed. (default 1)
setOptions in interface OptionHandlersetOptions in class Classifieroptions - 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 OptionHandlergetOptions in class Classifierpublic Capabilities getCapabilities()
getCapabilities in interface CapabilitiesHandlergetCapabilities in class ClassifierCapabilities
public void buildClassifier(Instances insts)
throws java.lang.Exception
buildClassifier in class Classifierinsts - the data to train the classifier with
java.lang.Exception - if something goes wrong during building
public void updateClassifier(Instance instance)
throws java.lang.Exception
updateClassifier in interface UpdateableClassifierinstance - the instance to update the classifier with
java.lang.Exception - if something goes wrong
public double classifyInstance(Instance inst)
throws java.lang.Exception
classifyInstance in class Classifierinst - the instance for which prediction is to be computed
java.lang.Exception - if something goes wrongpublic java.lang.String toString()
toString in class java.lang.Objectpublic java.lang.String balancedTipText()
public boolean getBalanced()
public void setBalanced(boolean b)
b - Value to assign to Balanced.public java.lang.String alphaTipText()
public double getAlpha()
public void setAlpha(double a)
a - Value to assign to Alpha.public java.lang.String betaTipText()
public double getBeta()
public void setBeta(double b)
b - Value to assign to Beta.public java.lang.String thresholdTipText()
public double getThreshold()
public void setThreshold(double t)
t - Value to assign to Threshold.public java.lang.String defaultWeightTipText()
public double getDefaultWeight()
public void setDefaultWeight(double w)
w - Value to assign to defaultWeight.public java.lang.String numIterationsTipText()
public int getNumIterations()
public void setNumIterations(int v)
v - Value to assign to numIterations.public java.lang.String seedTipText()
public int getSeed()
public void setSeed(int v)
v - Value to assign to Seed.public java.lang.String getRevision()
getRevision in interface RevisionHandlergetRevision in class Classifierpublic static void main(java.lang.String[] argv)
argv - the commandline options
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