Package | Description |
---|---|
at.tuwien.ifs.feature.evaluation | |
at.tuwien.ifs.somtoolbox.apps |
Classes in this package implement applications based upon SOMs, the most important being the
SOMViewer . |
at.tuwien.ifs.somtoolbox.apps.analysis | |
at.tuwien.ifs.somtoolbox.apps.helper | |
at.tuwien.ifs.somtoolbox.apps.initEval | |
at.tuwien.ifs.somtoolbox.apps.viewer |
This package implements the SOMViewer application; main class is SOMViewer.java.
|
at.tuwien.ifs.somtoolbox.data |
Classes in this package implement reading, storing and providing of different data needed for the SOM, e.g.
|
at.tuwien.ifs.somtoolbox.data.distance | |
at.tuwien.ifs.somtoolbox.data.normalisation | |
at.tuwien.ifs.somtoolbox.database |
Classes providing the connection to and reading from or writing to a database.
|
at.tuwien.ifs.somtoolbox.input |
Provides classes responsible for reading trained network models from file or some other location.
|
at.tuwien.ifs.somtoolbox.layers |
Provides the basic classes constituting SOM-based neural networks.
|
at.tuwien.ifs.somtoolbox.layers.initialisation | |
at.tuwien.ifs.somtoolbox.layers.quality |
Classes in this package implement various quality measures, indicating the quality of the SOM mapping.
|
at.tuwien.ifs.somtoolbox.models |
Provides the actual implementations of network models.
|
at.tuwien.ifs.somtoolbox.output |
Provides classes to write trained SOMs to files for future re-use.
|
at.tuwien.ifs.somtoolbox.output.labeling |
Provides implementations of labeling algorithms to assign semantic labels to SOM units.
|
at.tuwien.ifs.somtoolbox.reportgenerator | |
at.tuwien.ifs.somtoolbox.summarisation.methods | |
at.tuwien.ifs.somtoolbox.summarisation.parser | |
at.tuwien.ifs.somtoolbox.visualization |
Provides classes creating visualisations of trained SOMs.
|
at.tuwien.ifs.somtoolbox.visualization.minimumSpanningTree |
Modifier and Type | Field and Description |
---|---|
private ArrayList<InputData> |
SimilarityRetrievalGUI.inputData |
Modifier and Type | Field and Description |
---|---|
private InputData |
SDHTrainingSequenceGenerator.data |
Modifier and Type | Field and Description |
---|---|
private InputData |
PlaylistAnalysis.inputData |
private InputData |
PLStepSequenceAnalyser.inputData |
private InputData |
PLInputSpaceAnalyser.inputData |
Modifier and Type | Method and Description |
---|---|
InputData |
PlaylistAnalysis.getInputData() |
Modifier and Type | Class and Description |
---|---|
class |
VectorFileToRandomAccessFileConverter
Converts an input file to a binary/random access input file.
|
Modifier and Type | Method and Description |
---|---|
private void |
DataMapper.mapCompleteDataAfterTraining(GrowingSOM som,
InputData data,
SOMLibClassInformation classInfo,
ArrayList<String> mappingExceptions,
String labelerName,
int numLabels) |
private static void |
DatasetRandomiser.writeToFile(String fileName,
InputData inputData,
int[] columnOrder,
int[] rowOrder,
boolean gzip) |
Modifier and Type | Field and Description |
---|---|
private static InputData |
Measure.inputData |
Modifier and Type | Method and Description |
---|---|
static InputData |
Measure.getInputData() |
Modifier and Type | Method and Description |
---|---|
static void |
Measure.setInputData(InputData data) |
Modifier and Type | Field and Description |
---|---|
private InputData |
ExportDialog.inputVector |
Modifier and Type | Class and Description |
---|---|
class |
AbstractSOMLibSparseInputData
This abstract implementation provides basic support for operating on a
InputData . |
class |
ARFFFormatInputData
Reads input data from a WEKA ARFF File Format.
|
class |
DataBaseSOMLibSparseInputData
Implements
InputData by reading the vector information from a database. |
class |
ESOMInputData
Reads a input data file in the ESOM format.
|
class |
Marsyas_0_4_5_ARFFInputData
Marsyas 0.4.5 writes, after the line with the label name as comment (see
MarsyasARFFInputData , an additional
line such as |
class |
MarsyasARFFInputData
A reader for the Marsyas 0.2 ARFF format, which has the label name as a comment in front of the vector file name.
|
class |
RandomAccessFileSOMLibInputData
Reads SOMLib input from a random access file.
|
class |
SimpleMatrixInputData
Reads data from a simple matrix file.
|
class |
SOMLibSparseInputData
Implements
InputData based on a SOMLib Input Vector File. |
class |
SOMLibSparseInputDataNames
Reads just the data names from the Input file, the rest is discarded.
|
class |
SOMPAKInputData
This class reads input vector data from files in the SOMPak format, as provided by the MATLAB SOMToolbox.
|
Modifier and Type | Method and Description |
---|---|
InputData |
SharedSOMVisualisationData.getInputData() |
static InputData |
InputDataFactory.open(String inputVectorFileName) |
static InputData |
InputDataFactory.open(String formatName,
String inputFileName) |
static InputData |
InputDataFactory.open(String vectorFileName,
String templateFileName,
boolean sparse,
boolean norm,
int numCacheBlocks,
long seed) |
InputData |
SimpleMatrixInputData.subset(String[] names) |
InputData |
SOMLibSparseInputData.subset(String[] names) |
InputData |
RandomAccessFileSOMLibInputData.subset(String[] names) |
InputData |
InputData.subset(String[] names)
Gets a subset of this input data set.
|
InputData |
DataBaseSOMLibSparseInputData.subset(String[] names)
TODO: this reads the whole subset into the memory.
|
Modifier and Type | Method and Description |
---|---|
static StringBuffer |
InputDataWriter.getAsWekaARFF(InputData data,
boolean writeInstanceNames,
boolean skipInputsWithoutClass,
String relationName) |
static StringBuffer |
InputDataWriter.getAsWekaARFFRandomized(InputData data,
boolean writeInstanceNames,
boolean skipInputsWithoutClass,
int randomSeed,
String relationName) |
static void |
RandomAccessFileSOMLibInputData.write(InputData data,
String outputFile) |
static void |
InputDataWriter.write(String fName,
InputData data,
String outputFormat,
boolean tabSeparatedClassFile,
boolean skipInstanceNames,
boolean skipInputsWithoutClass) |
static void |
InputDataWriter.writeAsCSV(InputData data,
String fileName) |
static void |
InputDataWriter.writeAsESOM(InputData data,
String fileName)
Writes the data to ESOM lrn/cls
format.
|
static void |
InputDataWriter.writeAsOrange(InputData data,
String fileName)
Writes input data in the tab-separated format used by the Orange data mining toolkit (see
http://www.ailab.si/orange/)
|
static void |
InputDataWriter.writeAsSOMLib(InputData data,
String fileName) |
static void |
InputDataWriter.writeAsSOMLib(InputData data,
TemplateVector templateVector,
SOMLibClassInformation classInformation,
boolean tabSeparatedClassFile,
String basicFileName)
Writes the class information to a file.
|
static void |
InputDataWriter.writeAsSOMLib(InputData data,
TemplateVector templateVector,
SOMLibClassInformation classInformation,
String basicFileName)
Writes the class information to a file.
|
static void |
InputDataWriter.writeAsSOMPAK(InputData data,
String fileName)
Writes input data in the SOMPAK format (see
http://www.cis.hut.fi/projects/somtoolbox/package/docs2/som_read_data.html)
|
private static void |
InputDataWriter.writeAsVowpalWobbit(InputData data,
String fileName) |
private static void |
InputDataWriter.writeAsWekaARFF(InputData data,
boolean writeInstanceNames,
boolean skipInputsWithoutClass,
PrintWriter writer,
String relationName) |
static void |
InputDataWriter.writeAsWekaARFF(InputData data,
String fileName,
boolean writeInstanceNames,
boolean skipInputsWithoutClass)
Writes the data to Weka ARFF format.
|
Modifier and Type | Method and Description |
---|---|
static void |
DistanceMatrixWriter.writeOrangeFileInputVectorDistanceMatrix(InputData data,
String fileName,
DistanceMetric metric)
Write input distance matrix to an ASCII file for the Orange data mining toolkit ((http://www.ailab.si/orange/),
computing distances on the fly.
|
static void |
DistanceMatrixWriter.writePlainFileInputVectorDistanceMatrix(InputData data,
String fileName,
DistanceMetric metric)
Write input distance matrix to an ASCII file in plain format, computing distances on the fly.
|
static void |
DistanceMatrixWriter.writeRandomAccessFileInputVectorDistanceMatrix(InputData data,
String fileName,
DistanceMetric metric)
Write input distance matrix to a binary file, computing distances on the fly.
|
static void |
DistanceMatrixWriter.writeSOMLibFileInputVectorDistanceMatrix(InputData data,
String fileName,
DistanceMetric metric)
Write input distance matrix to ASCII file, computing distances on the fly.
|
static void |
DistanceMatrixWriter.writeSOMLibFileInputVectorDistanceMatrix(InputData data,
String fileName,
DistanceMetric metric,
boolean gzip)
Write input distance matrix to ASCII file, computing distances on the fly.
|
Constructor and Description |
---|
AbstractMemoryInputVectorDistanceMatrix(InputData data,
DistanceMetric metric)
Constructs the distance matrix by computing the distances on the fly.
|
FullMemoryInputVectorDistanceMatrix(InputData data,
DistanceMetric metric) |
LeightWeightMemoryInputVectorDistanceMatrix(InputData data,
DistanceMetric metric) |
Modifier and Type | Class and Description |
---|---|
(package private) class |
AbstractNormaliser |
class |
MinMaxNormaliser
Min-max normalisation, normalises the attributes between 0 and 1.
|
class |
StandardScoreNormaliser
Standard score nomalisation, normalises the attributes to have zero mean and the standard deviation as max values,
i.e.
|
class |
UnitLengthNormaliser
Unit length normalisation, normalises the length of the instance to 1.
|
Modifier and Type | Class and Description |
---|---|
private class |
VectorFile2DatabaseImporter.InputVectorImporter
This class customises the handling of data read from the file by storing it in the DB.
|
Modifier and Type | Method and Description |
---|---|
void |
InputCorrections.readFromFile(String fileName,
Layer layer,
InputData data) |
Constructor and Description |
---|
InputCorrections(String fileName,
Layer layer,
InputData data) |
Modifier and Type | Field and Description |
---|---|
private InputData |
GrowingLayer.data |
private InputData |
GrowingCellLayer.data
Data used for training
|
Modifier and Type | Method and Description |
---|---|
InputData |
GrowingLayer.getData() |
InputData |
GrowingCellLayer.getData() |
Modifier and Type | Method and Description |
---|---|
void |
Unit.addMappedInput(InputData data,
boolean calcQE)
Map all the input vectors contained in specified
InputData object onto this unit. |
InputCorrections |
GrowingLayer.computeUnitFeatureWeights(InputCorrections corrections,
InputData data,
Unit.FeatureWeightMode mode)
Implementation of general weighting as in Nünrberger/Detyniecki, 'Weighted Self-Organizing Maps: Incorporating
User Feedback'
|
String[] |
GrowingLayer.getNNearestInputs(String datumlabel,
int n,
InputData data) |
private void |
GrowingCellLayer.mapCompleteData(InputData data)
Maps data to the units
|
private void |
GrowingLayer.mapCompleteDataAfterTraining(InputData data)
Maps data onto layer without recalculating the quantization error after every single input datum.
FIXME: add multi-threading |
void |
GrowingLayer.mapData(InputData data)
Maps input data onto layer.
|
String |
Unit.printUnitDetails(InputData inputData,
TemplateVector tv) |
QualityMeasure |
GrowingLayer.train(InputData data,
double initialLearnrate,
double initialSigma,
int numIterations,
double tau,
double targetQualityValue,
String qualityMeasureName,
SOMProperties trainingProps)
Trains the layer with the input data.
|
QualityMeasure |
GrowingLayer.train(InputData data,
double iniLearnrate,
double iniSigma,
int numIterations,
double tau,
String qualityMeasureName,
SOMProperties trainingProps)
Trains the layer with the input data.
|
QualityMeasure |
GrowingLayer.train(InputData data,
double initialLearnrate,
double initialSigma,
int numIterations,
int startIteration,
double tau,
double targetQualityValue,
String qualityMeasureName,
SOMProperties trainingProps)
Trains the layer with the input data.
|
QualityMeasure |
GrowingLayer.train(InputData data,
double iniLearnrate,
double iniSigma,
int numIterations,
int startIteration,
double tau,
String qualityMeasureName,
SOMProperties trainingProps)
Trains the layer with the input data.
|
QualityMeasure |
GrowingCellLayer.train(InputData data,
float epsilonB,
float epsilonN,
float alpha,
int lamda,
float eta,
SOMProperties props)
Trains the CellLayer with the given Parameters and returns the QualityMeasure
|
private void |
GrowingLayer.trainNormal(InputData data,
int numIterations,
int startIteration,
SOMProperties trainingProps,
double initialLearnrate,
double initialSigma,
double expParam,
double expParam2,
ProgressListener progressWriter) |
private void |
GrowingCellLayer.trainNormal(InputData data,
ProgressListener progressWriter)
Trains the CellLayer with the secified InputData and logs to progressWriter
|
private void |
GrowingLayer.trainSpecial(InputData data,
int numIterations,
int startIteration,
SOMProperties trainingProps,
double initialLearnrate,
double initialSigma,
double expParam,
double expParam2,
SOMLibClassInformation classInfo,
double minProbability,
ProgressListener progressWriter) |
Constructor and Description |
---|
GrowingCellLayer(int dim,
boolean normalize,
long randomSeed,
InputData data)
Std.
|
GrowingLayer(int xSize,
int ySize,
int zSize,
String metricName,
int dim,
boolean normalized,
boolean usePCA,
long seed,
InputData data)
Convenience constructor for top layer map of GHSOM or a single map.
|
GrowingLayer(int xSize,
int ySize,
String metricName,
int dim,
boolean normalized,
boolean usePCA,
long seed,
InputData data)
Convenience constructor for top layer map of GHSOM or a single map.
|
GrowingLayer(int id,
Unit su,
int xSize,
int ySize,
int zSize,
String metricName,
int dim,
boolean normalized,
boolean usePCA,
long seed,
InputData data)
Constructor for a new, untrained layer.
|
GrowingLayer(int id,
Unit su,
int xSize,
int ySize,
String metricName,
int dim,
boolean normalized,
boolean usePCA,
long seed,
InputData data)
Constructor for a new, untrained layer.
|
ToroidLayer(int xSize,
int ySize,
int zSize,
String metricName,
int dim,
boolean normalize,
boolean usePCA,
long seed,
InputData data) |
ToroidLayer(int xSize,
int ySize,
String metricName,
int dim,
boolean normalize,
boolean usePCA,
long seed,
InputData data) |
ToroidLayer(int id,
Unit su,
int xSize,
int ySize,
int zSize,
String metricName,
int dim,
boolean normalize,
boolean usePCA,
long seed,
InputData data) |
ToroidLayer(int id,
Unit su,
int xSize,
int ySize,
String metricName,
int dim,
boolean normalize,
boolean usePCA,
long seed,
InputData data) |
Modifier and Type | Field and Description |
---|---|
private InputData |
PCAInitializer.data |
Constructor and Description |
---|
PCAInitializer(Layer layer,
int size,
int size2,
int size3,
InputData data,
int dim) |
RandomSamplingInitializer(Layer layer,
int xSize,
int ySize,
int zSize,
InputData data) |
Modifier and Type | Field and Description |
---|---|
(package private) InputData |
TopographicFunction.data |
protected InputData |
AbstractQualityMeasure.data |
Modifier and Type | Method and Description |
---|---|
static QualityMeasure |
AbstractQualityMeasure.instantiate(String qmName,
Layer layer,
InputData data)
Instantiates a certain quality measure class specified by argument
mqName . |
Constructor and Description |
---|
AbstractQualityMeasure(Layer layer,
InputData data) |
EntropyMeasure(Layer layer,
InputData data) |
IntrinsicDistance(Layer layer,
InputData data) |
InversionMeasure(Layer layer,
InputData data) |
MetricMultiScaling(Layer layer,
InputData data) |
PseudoSilhouetteValue(Layer layer,
InputData data) |
QuantizationError(Layer layer,
InputData data) |
SammonMeasure(Layer layer,
InputData data) |
SilhouetteValue(Layer layer,
InputData data) |
SOMDistortion(Layer layer,
InputData data) |
SOMSilhouetteValue(Layer layer,
InputData data) |
SpearmanCoefficient(Layer layer,
InputData data) |
TopographicError(Layer layer,
InputData data) |
TopographicFunction(Layer layer,
InputData data) |
TopographicProduct(Layer layer,
InputData data) |
Trustworthiness_NeighborhoodPreservation(Layer layer,
InputData data) |
Modifier and Type | Method and Description |
---|---|
protected static InputData |
AbstractNetworkModel.getInputData(FileProperties fileProps) |
Modifier and Type | Method and Description |
---|---|
private void |
GrowingSOM.initLayer(boolean norm,
SOMProperties props,
InputData data) |
void |
GHSOM.train(InputData data,
GHSOMProperties props)
Trains the GHSOM with the input data and training parameters specified in the properties provided by argument
props . |
QualityMeasure |
GrowingSOM.train(InputData data,
GHSOMProperties props,
double targetQualityValue,
String qualityMeasureName)
Trains the map with the input data and training parameters specified in the properties provided by argument
props . |
void |
GrowingSOM.train(InputData data,
SOMProperties props)
Trains the map with the input data and training parameters specified in the properties provided by argument
props . |
private void |
GrowingCellStructures.train(InputData data,
SOMProperties props)
Trains a GrowingCellStructures
|
Constructor and Description |
---|
GHSOM(int dim,
boolean norm,
GHSOMProperties props,
InputData data)
Constructs a new
GHSOM with dim -dimensional weight vectors. |
GrowingCellStructures(int dim,
boolean normalize,
SOMProperties props,
InputData data)
Constructs a new
GrowingCellStructures with dim -dimensional weight vectors. |
GrowingSOM(boolean norm,
SOMProperties props,
InputData data)
Constructs a new
GrowingSOM with dim -dimensional weight vectors. |
GrowingSOM(int xSize,
int ySize,
int numIterations,
InputData data)
Constructs and trains a new
GrowingSOM . |
GrowingSOM(int xSize,
int ySize,
int zSize,
String metricName,
int numIterations,
boolean normalised,
boolean usePCAInit,
int randomSeed,
InputData data)
Constructs and trains a new
GrowingSOM . |
GrowingSOM(int id,
Unit su,
int dim,
boolean norm,
SOMProperties props,
InputData data)
Constructs a new
GrowingSOM with dim -dimensional weight vectors. |
Modifier and Type | Method and Description |
---|---|
static void |
ESOMMapOutputter.write(GrowingSOM gsom,
InputData data,
String dir,
String fileName,
boolean gzipped) |
static void |
SOMLibMapOutputter.writeDataWinnerMappingFile(GHSOM ghsom,
InputData data,
int numWinners,
String fDir,
String fName,
boolean gzipped) |
static void |
GrowingCellStructuresMapOutputter.writeDataWinnerMappingFile(GrowingCellStructures csom,
InputData data,
int numWinners,
String fDir,
String fName,
boolean gzipped) |
static void |
SOMLibMapOutputter.writeDataWinnerMappingFile(GrowingSOM gsom,
InputData data,
int numWinners,
String fDir,
String fName,
boolean gzipped) |
Modifier and Type | Method and Description |
---|---|
protected int |
AbstractLabeler.checkMaxDimensionality(InputData data,
int num) |
private UnitWordsMap |
LagusKeywordLabeler.generateUnitWordsMap(Unit[] units,
GrowingSOM gsom,
InputData data,
TemplateVector tv) |
void |
LagusKeywordLabeler.label(GHSOM ghsom,
InputData data,
int num) |
void |
Labeler.label(GHSOM ghsom,
InputData data,
int num) |
void |
LabelSOM.label(GHSOM ghsom,
InputData data,
int num) |
void |
LagusKeywordLabeler.label(GrowingSOM gsom,
InputData data,
int num) |
void |
Labeler.label(GrowingSOM gsom,
InputData data,
int num)
Determines and adds labels to the units of a GrowingSOM (should be NetworkModel in the future).
|
void |
LabelSOM.label(GrowingSOM gsom,
InputData data,
int num) |
void |
LagusKeywordLabeler.label(GrowingSOM gsom,
InputData data,
int num,
boolean ignoreLabelsWithZero) |
void |
Labeler.label(GrowingSOM gsom,
InputData data,
int num,
boolean ignoreLabelsWithZero) |
void |
LabelSOM.label(GrowingSOM gsom,
InputData data,
int num,
boolean ignoreLabelsWithZero) |
Modifier and Type | Field and Description |
---|---|
private InputData |
DatasetInformation.inputData |
Modifier and Type | Method and Description |
---|---|
InputData |
DatasetInformation.getInputData()
returns the InputData object storing information about the input data used for training the som.
|
Modifier and Type | Field and Description |
---|---|
private InputData |
TFxIDF.inputVector |
Modifier and Type | Method and Description |
---|---|
void |
TFxIDF.setVectors(InputData input,
SOMLibTemplateVector template) |
void |
CombinedMethod.setVectors(InputData input,
SOMLibTemplateVector template) |
Modifier and Type | Field and Description |
---|---|
private InputData |
Scorer.inputvectors |
Constructor and Description |
---|
Scorer(Object[] itemN,
InputData input,
SOMLibTemplateVector template) |
Scorer(String itemN,
InputData input,
SOMLibTemplateVector template) |
Modifier and Type | Field and Description |
---|---|
private InputData |
NeighbourhoodGraph.inputData |
private InputData |
ActivityHistogram.inputData |
Constructor and Description |
---|
ActivityHistogram.ActivityHistrogramControlPanel(ActivityHistogram hist,
InputData inputData) |
Modifier and Type | Field and Description |
---|---|
(package private) InputData |
InputdataGraph.data |