public class LogisticBase extends Classifier implements WeightedInstancesHandler
-D If set, classifier is run in debug mode and may output additional info to the console
Constructor and Description |
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LogisticBase()
Constructor that creates LogisticBase object with standard options.
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LogisticBase(int numBoostingIterations,
boolean useCrossValidation,
boolean errorOnProbabilities)
Constructor to create LogisticBase object.
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Modifier and Type | Method and Description |
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void |
buildClassifier(Instances data)
Builds the logistic regression model usiing LogitBoost.
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void |
cleanup()
Cleanup in order to save memory.
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double[] |
distributionForInstance(Instance instance)
Returns class probabilities for an instance.
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int |
getMaxIterations()
Returns the maxIterations parameter.
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int |
getNumRegressions()
The number of LogitBoost iterations performed (= the number of simple
regression functions fit).
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java.lang.String |
getRevision()
Returns the revision string.
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boolean |
getUseAIC()
Get the value of useAIC.
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int[][] |
getUsedAttributes()
Returns an array of the indices of the attributes used in the logistic model.
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double |
getWeightTrimBeta()
Get the value of weightTrimBeta.
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double |
percentAttributesUsed()
Returns the fraction of all attributes in the data that are used in the
logistic model (in percent).
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void |
setHeuristicStop(int heuristicStop)
Sets the option "heuristicStop".
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void |
setMaxIterations(int maxIterations)
Sets the parameter "maxIterations".
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void |
setUseAIC(boolean c)
Set the value of useAIC.
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void |
setWeightTrimBeta(double w)
Sets the option "weightTrimBeta".
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java.lang.String |
toString()
Returns a description of the logistic model (i.e., attributes and
coefficients).
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classifyInstance, debugTipText, forName, getCapabilities, getDebug, getOptions, listOptions, makeCopies, makeCopy, setDebug, setOptions
public LogisticBase()
public LogisticBase(int numBoostingIterations, boolean useCrossValidation, boolean errorOnProbabilities)
numBoostingIterations
- fixed number of iterations for LogitBoost (if negative, use cross-validation or
stopping criterion on the training data).useCrossValidation
- cross-validate number of LogitBoost iterations (if false, use stopping
criterion on the training data).errorOnProbabilities
- if true, use error on probabilities
instead of misclassification for stopping criterion of LogitBoostpublic void buildClassifier(Instances data) throws java.lang.Exception
buildClassifier
in class Classifier
data
- the training datajava.lang.Exception
- if something goes wrongpublic int[][] getUsedAttributes()
public int getNumRegressions()
public double getWeightTrimBeta()
public boolean getUseAIC()
public void setMaxIterations(int maxIterations)
maxIterations
- the maximum iterationspublic void setHeuristicStop(int heuristicStop)
heuristicStop
- the heuristic stop to usepublic void setWeightTrimBeta(double w)
public void setUseAIC(boolean c)
c
- Value to assign to useAIC.public int getMaxIterations()
public double percentAttributesUsed()
public java.lang.String toString()
toString
in class java.lang.Object
public double[] distributionForInstance(Instance instance) throws java.lang.Exception
distributionForInstance
in class Classifier
instance
- the instance to compute the distribution forjava.lang.Exception
- if distribution can't be computed successfullypublic void cleanup()
public java.lang.String getRevision()
getRevision
in interface RevisionHandler
getRevision
in class Classifier