V
- vector type@Alias(value={"de.lmu.ifi.dbs.elki.datasource.filter.normalization.AttributeWiseMinMaxNormalization","de.lmu.ifi.dbs.elki.datasource.filter.AttributeWiseMinMaxNormalization"}) public class AttributeWiseMinMaxNormalization<V extends NumberVector> extends AbstractNormalization<V>
Modifier and Type | Class and Description |
---|---|
static class |
AttributeWiseMinMaxNormalization.Parameterizer<V extends NumberVector>
Parameterization class.
|
Modifier and Type | Field and Description |
---|---|
private static Logging |
LOG
Class logger.
|
private double[] |
maxima
Stores the maximum in each dimension.
|
private double[] |
minima
Stores the minimum in each dimension.
|
factory
Constructor and Description |
---|
AttributeWiseMinMaxNormalization(double[] minima,
double[] maxima)
Constructor.
|
Modifier and Type | Method and Description |
---|---|
private double |
factor(int dimension)
Returns a factor for normalization in a certain dimension.
|
protected V |
filterSingleObject(V featureVector)
Normalize a single instance.
|
protected SimpleTypeInformation<? super V> |
getInputTypeRestriction()
Get the input type restriction used for negotiating the data query.
|
protected Logging |
getLogger()
Class logger.
|
protected void |
prepareProcessInstance(V featureVector)
Process a single object during initialization.
|
protected boolean |
prepareStart(SimpleTypeInformation<V> in)
Return "true" when the normalization needs initialization (two-pass filtering!).
|
V |
restore(V featureVector)
Transforms a feature vector to the original attribute ranges.
|
String |
toString() |
LinearEquationSystem |
transform(LinearEquationSystem linearEquationSystem)
Transforms a linear equation system describing linear dependencies
derived on the normalized space into a linear equation system describing
linear dependencies quantitatively adapted to the original space.
|
convertedType
initializeOutputType
filter, prepareComplete
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
filter
private static final Logging LOG
private double[] maxima
private double[] minima
public AttributeWiseMinMaxNormalization(double[] minima, double[] maxima)
minima
- Minimum valuesmaxima
- Maximum valuesprotected boolean prepareStart(SimpleTypeInformation<V> in)
AbstractConversionFilter
prepareStart
in class AbstractConversionFilter<V extends NumberVector,V extends NumberVector>
in
- Input type informationprotected void prepareProcessInstance(V featureVector)
AbstractConversionFilter
prepareProcessInstance
in class AbstractConversionFilter<V extends NumberVector,V extends NumberVector>
featureVector
- Object to processprotected V filterSingleObject(V featureVector)
AbstractConversionFilter
filterSingleObject
in class AbstractConversionFilter<V extends NumberVector,V extends NumberVector>
featureVector
- Database object to normalizepublic V restore(V featureVector) throws NonNumericFeaturesException
Normalization
restore
in interface Normalization<V extends NumberVector>
restore
in class AbstractNormalization<V extends NumberVector>
featureVector
- a feature vector to be transformed into original spaceNonNumericFeaturesException
- feature vector is not compatible with values initialized
during normalizationprivate double factor(int dimension)
dimension
- the dimension to get a factor for normalizationpublic LinearEquationSystem transform(LinearEquationSystem linearEquationSystem)
Normalization
transform
in interface Normalization<V extends NumberVector>
transform
in class AbstractNormalization<V extends NumberVector>
linearEquationSystem
- the linear equation system to be transformedpublic String toString()
toString
in class AbstractNormalization<V extends NumberVector>
protected Logging getLogger()
AbstractConversionFilter
getLogger
in class AbstractConversionFilter<V extends NumberVector,V extends NumberVector>
protected SimpleTypeInformation<? super V> getInputTypeRestriction()
AbstractConversionFilter
getInputTypeRestriction
in class AbstractConversionFilter<V extends NumberVector,V extends NumberVector>
Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.