C D G H I J N O P R S T V

C

classifyDataset(IDataset) - Method in interface JavaML.IClassifier
 
classifyDataset(IDataset) - Method in class JavaML.NaiveBayes
Returns the classifications made by the trained classifier on the testing data
classifyDataset(IDataset) - Method in class JavaML.OnlineAdaBoost
Returns the classifications made by the trained classifier on the testing data
classifyDataset(IDataset) - Method in class JavaML.OnlineBinaryClassifier
Returns the classifications made by the trained classifier on the testing data
classifyDataset(IDataset) - Method in class JavaML.ONSBoost
Returns the classifications made by the trained classifier on the testing data
classifySample(double[]) - Method in interface JavaML.IClassifier
 
classifySample(double[]) - Method in class JavaML.NaiveBayes
Returns the classification for a single example
classifySample(double[]) - Method in class JavaML.OnlineAdaBoost
Returns the classification for a single example
classifySample(double[]) - Method in class JavaML.OnlineBinaryClassifier
Returns the classification for a single example
classifySample(double[]) - Method in class JavaML.ONSBoost
Returns the classification for a single example
copyClassifier() - Method in interface JavaML.IClassifier
 
copyClassifier() - Method in interface JavaML.IOnlineClassifier
 
copyClassifier() - Method in class JavaML.NaiveBayes
Copy constructor, used by the ensemble algorithms
copyClassifier() - Method in class JavaML.OnlineAdaBoost
Copy constructor
copyClassifier() - Method in class JavaML.OnlineBinaryClassifier
Copy constructor, used by the ensemble algorithms
copyClassifier() - Method in class JavaML.ONSBoost
Copy constructor

D

DatasetDouble - Class in JavaML
An implementation of IDataset using doubles
DatasetDouble(String, boolean, boolean) - Constructor for class JavaML.DatasetDouble
Constructor from file
DatasetDouble(double[][], int[]) - Constructor for class JavaML.DatasetDouble
Constructor from data
DatasetDouble(double[][], int[], double[], int) - Constructor for class JavaML.DatasetDouble
Constructor from weighted data

G

getDataFeatureSubset(int[]) - Method in class JavaML.DatasetDouble
Returns a new IDataset which contains a subset of the features of the original
getDataFeatureSubset(int[]) - Method in interface JavaML.IDataset
 
getDataMatrixDouble() - Method in class JavaML.DatasetDouble
 
getDataMatrixDouble() - Method in interface JavaML.IDataset
 
getDataSampleSubset(int[]) - Method in class JavaML.DatasetDouble
Returns a new IDataset which contains a subset of the samples of the original
getDataSampleSubset(int[]) - Method in interface JavaML.IDataset
 
getDataType() - Method in class JavaML.DatasetDouble
 
getDataType() - Method in interface JavaML.IOnlineDataset
 
getDataWeights() - Method in class JavaML.DatasetDouble
 
getDataWeights() - Method in interface JavaML.IDataset
 
getFeatureList() - Method in interface JavaML.IClassifier
 
getFeatureList() - Method in class JavaML.NaiveBayes
 
getFeatureList() - Method in class JavaML.OnlineAdaBoost
Returns the list of features used by each weak learner (useful for decision stumps)
getFeatureList() - Method in class JavaML.OnlineBinaryClassifier
 
getFeatureList() - Method in class JavaML.ONSBoost
Returns the list of features used by each weak learner (useful for decision stumps)
getIsTrained() - Method in interface JavaML.IClassifier
 
getIsTrained() - Method in class JavaML.NaiveBayes
 
getIsTrained() - Method in class JavaML.OnlineAdaBoost
 
getIsTrained() - Method in class JavaML.OnlineBinaryClassifier
 
getIsTrained() - Method in class JavaML.ONSBoost
 
getNextDataPoint() - Method in class JavaML.DatasetDouble
 
getNextDataPoint() - Method in interface JavaML.IOnlineDataset
 
getNextTarget() - Method in class JavaML.DatasetDouble
 
getNextTarget() - Method in interface JavaML.IOnlineDataset
 
getNumberOfFeatures() - Method in class JavaML.DatasetDouble
 
getNumberOfFeatures() - Method in interface JavaML.IOnlineDataset
 
getNumberOfSamples() - Method in class JavaML.DatasetDouble
 
getNumberOfSamples() - Method in interface JavaML.IOnlineDataset
 
getSampledDataset(double[], int) - Method in class JavaML.DatasetDouble
Returns a new IDataset a sampled version of the original, based upon the supplied distribution over examples
getSampledDataset(double[], int) - Method in interface JavaML.IDataset
 
getSampleDouble(int, boolean) - Method in class JavaML.DatasetDouble
 
getSampleDouble(int, boolean) - Method in interface JavaML.IDataset
 
getTargetVector() - Method in class JavaML.DatasetDouble
 
getTargetVector() - Method in interface JavaML.IDataset
 
getTotalWeight() - Method in class JavaML.DatasetDouble
 
getTotalWeight() - Method in interface JavaML.IDataset
 

H

hasData() - Method in class JavaML.DatasetDouble
 
hasData() - Method in interface JavaML.IOnlineDataset
 

I

IClassifier - Interface in JavaML
An interface for representing a Classifier
IDataset - Interface in JavaML
An interface for representing a Dataset It extends IOnlineDataset as it imposes several properties, such as the whole dataset being accesible at once.
IOnlineClassifier - Interface in JavaML
An interface for representing an Online Classifier.
IOnlineDataset - Interface in JavaML
An interface for representing an Online Dataset
IOnlineDataset.DataType - Enum in JavaML
 
IOnlineDataset.FeatureType - Enum in JavaML
 

J

JavaML - package JavaML
 

N

NaiveBayes - Class in JavaML
An Online implementation of a two-class Naive Bayes Classifier, Compiler warnings are due to the generics implementation in Java not allowing arrays of a generic collection
NaiveBayes() - Constructor for class JavaML.NaiveBayes
Constructor, by default without psuedoCounts
NaiveBayes(boolean) - Constructor for class JavaML.NaiveBayes
Constructor, pseudoCounts is set to the value of newCounts
negativeClass - Static variable in interface JavaML.IClassifier
 

O

OnlineAdaBoost - Class in JavaML
An implementation of Online Boosting.
OnlineAdaBoost() - Constructor for class JavaML.OnlineAdaBoost
Constructor, needs to be supplied with a weak learner before training
OnlineAdaBoost(int, IOnlineClassifier, String, boolean) - Constructor for class JavaML.OnlineAdaBoost
Constructor, initialises everything required
OnlineAdaBoost(int, IOnlineClassifier, int, String, boolean) - Constructor for class JavaML.OnlineAdaBoost
Constructor, initialises everything required
OnlineBinaryClassifier - Class in JavaML
An Online implementation of a two-class Binary stump
OnlineBinaryClassifier() - Constructor for class JavaML.OnlineBinaryClassifier
 
onlineTrain(double[], int) - Method in interface JavaML.IOnlineClassifier
 
onlineTrain(double[], int) - Method in class JavaML.NaiveBayes
Is the online train function, which takes a single example and trains on it then returns the classification.
onlineTrain(double[], int) - Method in class JavaML.OnlineAdaBoost
Is the online train function, which takes a single example and trains on it then returns the classification.
onlineTrain(double[], int) - Method in class JavaML.OnlineBinaryClassifier
Is the online train function, which takes a single example and trains on it then returns the classification.
onlineTrain(double[], int) - Method in class JavaML.ONSBoost
Is the online train function, which takes a single example and trains on it then returns the classification.
ONSBoost - Class in JavaML
An implementation of ONSBoost.
ONSBoost() - Constructor for class JavaML.ONSBoost
Constructor, needs to be supplied with a weak learner before training
ONSBoost(int, IOnlineClassifier, String) - Constructor for class JavaML.ONSBoost
Constructor, initialises everything required
ONSBoost(int, IOnlineClassifier, int, String) - Constructor for class JavaML.ONSBoost
Constructor, initialises everything required

P

positiveClass - Static variable in interface JavaML.IClassifier
 

R

resetDataset() - Method in class JavaML.DatasetDouble
 
resetDataset() - Method in interface JavaML.IOnlineDataset
 
returnCurrentDataSampleNumber() - Method in class JavaML.DatasetDouble
 
returnCurrentDataSampleNumber() - Method in interface JavaML.IOnlineDataset
 
returnCurrentTargetSampleNumber() - Method in class JavaML.DatasetDouble
 
returnCurrentTargetSampleNumber() - Method in interface JavaML.IOnlineDataset
 
returnSampledTestingSet(int, int) - Method in class JavaML.DatasetDouble
Returns a new dataset containing fold foldNumber, by sampling from the weight distribution
returnSampledTestingSet(int, int) - Method in interface JavaML.IDataset
 
returnSampledTrainingSet(int, int) - Method in class JavaML.DatasetDouble
Returns a new dataset without fold foldNumber, by sampling from the weight distribution
returnSampledTrainingSet(int, int) - Method in interface JavaML.IDataset
 
returnWeightedTestingSet(int) - Method in class JavaML.DatasetDouble
Returns a new dataset containing fold foldNumber
returnWeightedTestingSet(int) - Method in interface JavaML.IDataset
 
returnWeightedTrainingSet(int) - Method in class JavaML.DatasetDouble
Returns a new dataset without fold foldNumber
returnWeightedTrainingSet(int) - Method in interface JavaML.IDataset
 

S

setDataWeights(double[]) - Method in class JavaML.DatasetDouble
Assigns the newWeights to the data weights.
setDataWeights(double[]) - Method in interface JavaML.IDataset
 
setRandomSeed(long) - Method in class JavaML.DatasetDouble
 
setRandomSeed(long) - Method in interface JavaML.IOnlineDataset
 
setRandomSeed(long) - Method in class JavaML.OnlineAdaBoost
 
setupClassifier(String) - Method in interface JavaML.IClassifier
 
setupClassifier(String) - Method in class JavaML.NaiveBayes
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.
setupClassifier(String) - Method in class JavaML.OnlineAdaBoost
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.
setupClassifier(String) - Method in class JavaML.OnlineBinaryClassifier
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.
setupClassifier(String) - Method in class JavaML.ONSBoost
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.
splitIntoFolds(int) - Method in class JavaML.DatasetDouble
Prepares the dataset to be split into newNumberOfFolds folds, all previous splits are forgotten MUST BE CALLED before using any other folds function
splitIntoFolds(int) - Method in interface JavaML.IDataset
 
supportsMultiClassData() - Method in interface JavaML.IClassifier
 
supportsMultiClassData() - Method in class JavaML.NaiveBayes
 
supportsMultiClassData() - Method in class JavaML.OnlineAdaBoost
 
supportsMultiClassData() - Method in class JavaML.OnlineBinaryClassifier
 
supportsMultiClassData() - Method in class JavaML.ONSBoost
 
supportsWeightedData() - Method in interface JavaML.IClassifier
 
supportsWeightedData() - Method in class JavaML.NaiveBayes
 
supportsWeightedData() - Method in class JavaML.OnlineAdaBoost
 
supportsWeightedData() - Method in class JavaML.OnlineBinaryClassifier
 
supportsWeightedData() - Method in class JavaML.ONSBoost
 

T

test(IDataset) - Method in interface JavaML.IClassifier
 
test(IDataset) - Method in class JavaML.NaiveBayes
Is the main offline test function, which takes an dataset and returns the testing error on that dataset
test(IDataset) - Method in class JavaML.OnlineAdaBoost
Is the main offline test function, which takes an dataset and returns the testing error on that dataset
test(IDataset) - Method in class JavaML.OnlineBinaryClassifier
Is the main offline test function, which takes an dataset and returns the testing error on that dataset
test(IDataset) - Method in class JavaML.ONSBoost
Is the main offline test function, which takes an dataset and returns the testing error on that dataset
train(IDataset, int) - Method in interface JavaML.IClassifier
 
train(IDataset, int) - Method in class JavaML.NaiveBayes
Is the main offline train function, which takes an dataset and trains on it in this classifier, iterations does nothing
train(IDataset, int) - Method in class JavaML.OnlineAdaBoost
Is the main offline train function, which takes an dataset and trains on it using offline AdaBoost
train(IDataset, int) - Method in class JavaML.OnlineBinaryClassifier
Is the main offline train function, which takes an dataset and trains on it in this classifier, iterations does nothing
train(IDataset, int) - Method in class JavaML.ONSBoost
Is the main offline train function, which takes an dataset and trains on it using the FloatBoost algorithm

V

valueOf(String) - Static method in enum JavaML.IOnlineDataset.DataType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum JavaML.IOnlineDataset.FeatureType
Returns the enum constant of this type with the specified name.
values() - Static method in enum JavaML.IOnlineDataset.DataType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum JavaML.IOnlineDataset.FeatureType
Returns an array containing the constants of this enum type, in the order they are declared.

C D G H I J N O P R S T V