Package | Description |
---|---|
at.tuwien.ifs.somtoolbox.apps.initEval | |
at.tuwien.ifs.somtoolbox.apps.trainer | |
at.tuwien.ifs.somtoolbox.layers |
Provides the basic classes constituting SOM-based neural networks.
|
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.
|
Modifier and Type | Field and Description |
---|---|
private static QualityMeasure |
Measure.qualitymeasure |
Modifier and Type | Method and Description |
---|---|
protected static QualityMeasure |
Measure.getQualityMeasure() |
Modifier and Type | Method and Description |
---|---|
static void |
Measure.setQualityMeasure(QualityMeasure qm) |
Modifier and Type | Field and Description |
---|---|
private ClassComboBoxModel<QualityMeasure> |
SOMTrainer.cmbQualityMeasureModel |
Modifier and Type | Method and Description |
---|---|
private ClassComboBoxModel<QualityMeasure> |
SOMTrainer.getCmbQualityMeasureModel() |
Modifier and Type | Field and Description |
---|---|
private QualityMeasure |
GrowingLayer.qualityMeasure |
private QualityMeasure |
GrowingCellLayer.qualityMeasure
QualityMesure used for GrowingCellStructures
|
Modifier and Type | Method and Description |
---|---|
QualityMeasure |
Layer.getQualityMeasure()
Returns the quality information.
|
QualityMeasure |
GrowingLayer.getQualityMeasure() |
QualityMeasure |
GrowingCellLayer.getQualityMeasure() |
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
|
Modifier and Type | Method and Description |
---|---|
private Unit |
GrowingLayer.getErrorUnit(QualityMeasure qm,
String methodName)
Returns the unit having the highest quantization error.
|
private void |
GrowingLayer.printInfo(double targetQualityValue,
String[] qmNameMethod,
QualityMeasure qm) |
Modifier and Type | Class and Description |
---|---|
class |
AbstractQualityMeasure
Provides basic functionality for quality measure algorithms.
|
class |
EntropyMeasure
Implementation of SOM Entropy Measure.
|
class |
IntrinsicDistance
Implementation of Intrinsic Distance Quality
|
class |
InversionMeasure
Implementation of SOM Inversion Measure for multidimenional Inputdata.
|
class |
MetricMultiScaling
Implementation of the SOM Metric Multidimensional Scaling Measure.
|
class |
PseudoSilhouetteValue |
class |
QuantizationError
Calculates the Quantisation Error, defined as the average distance between and input data vector and the
weight-vector of its best-matching-unit.
Calculates the following values: Unit Quantisation error (qe). |
class |
SammonMeasure
Sammon Measure for Self Organizing Maps (Sammon 1969)
|
class |
SilhouetteValue |
class |
SOMDistortion
Implementation of SOM Distortion Measure Quality.
|
class |
SOMSilhouetteValue |
class |
SpearmanCoefficient
Implementation of SOM Spearman Coeffizient.
|
class |
TopographicError
Implementation of Topographic Error Quality Measure.
TODO: can maybe be optimised using data winner mapping file ( SOMLibDataWinnerMapping ). |
class |
TopographicProduct
Implementation of Topographic Product Quality Measure.
More Infos: H.U. |
class |
Trustworthiness_NeighborhoodPreservation
Implematation of Trustworthiness and Neighborhood preservation Quality Measures
|
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 . |
Modifier and Type | Method and Description |
---|---|
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 . |
Modifier and Type | Method and Description |
---|---|
GHSOM.ExpandedUnits |
GHSOM.getExpandedUnits(GrowingLayer layer,
QualityMeasure qm,
String qmName,
double fraction,
double totalQuality) |