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java.lang.ObjectJavaML.OnlineBinaryClassifier
public class OnlineBinaryClassifier
An Online implementation of a two-class Binary stump
Field Summary |
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Fields inherited from interface JavaML.IClassifier |
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negativeClass, positiveClass |
Constructor Summary | |
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OnlineBinaryClassifier()
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Method Summary | |
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int[] |
classifyDataset(IDataset testingData)
Returns the classifications made by the trained classifier on the testing data |
int |
classifySample(double[] sample)
Returns the classification for a single example |
IOnlineClassifier |
copyClassifier()
Copy constructor, used by the ensemble algorithms |
int[] |
getFeatureList()
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boolean |
getIsTrained()
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int |
onlineTrain(double[] trainingData,
int target)
Is the online train function, which takes a single example and trains on it then returns the classification. |
void |
setupClassifier(java.lang.String arguments)
setupClassifier is used to modify classifiers after they have been constructed through the copy constructor, at that point you could either do reflection to figure out the class and reconstruct it, or you could pass it a string of arguments and have it reconfigure itself. |
boolean |
supportsMultiClassData()
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boolean |
supportsWeightedData()
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double |
test(IDataset testingData)
Is the main offline test function, which takes an dataset and returns the testing error on that dataset |
double |
train(IDataset trainingData,
int iterations)
Is the main offline train function, which takes an dataset and trains on it in this classifier, iterations does nothing |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
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public OnlineBinaryClassifier()
Method Detail |
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public IOnlineClassifier copyClassifier()
copyClassifier
in interface IClassifier
copyClassifier
in interface IOnlineClassifier
public void setupClassifier(java.lang.String arguments)
setupClassifier
in interface IClassifier
arguments
- a space separated list of parameter=value tuples.public double train(IDataset trainingData, int iterations)
train
in interface IClassifier
trainingData
- A training datasetiterations
- Does nothing (there for IClassifier support for Boosting)public int onlineTrain(double[] trainingData, int target)
onlineTrain
in interface IOnlineClassifier
trainingData
- A training sampletarget
- class label for the samplepublic double test(IDataset testingData)
test
in interface IClassifier
testingData
- A testing datasetpublic int[] classifyDataset(IDataset testingData)
classifyDataset
in interface IClassifier
testingData
- A testing datasetpublic int classifySample(double[] sample)
classifySample
in interface IClassifier
sample
- A testing samplepublic int[] getFeatureList()
getFeatureList
in interface IClassifier
public boolean getIsTrained()
getIsTrained
in interface IClassifier
public boolean supportsWeightedData()
supportsWeightedData
in interface IClassifier
public boolean supportsMultiClassData()
supportsMultiClassData
in interface IClassifier
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