Uses of Package
de.lmu.ifi.dbs.elki.datasource.filter

Packages that use de.lmu.ifi.dbs.elki.datasource.filter
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation Correlation clustering algorithms 
de.lmu.ifi.dbs.elki.data.model Cluster models classes for various algorithms. 
de.lmu.ifi.dbs.elki.datasource Data normalization (and reconstitution) of data sets. 
de.lmu.ifi.dbs.elki.datasource.filter Data filtering, in particular for normalization and projection. 
 

Classes in de.lmu.ifi.dbs.elki.datasource.filter used by de.lmu.ifi.dbs.elki.algorithm.clustering.correlation
NonNumericFeaturesException
          An exception to signal the encounter of non numeric features where numeric features have been expected.
 

Classes in de.lmu.ifi.dbs.elki.datasource.filter used by de.lmu.ifi.dbs.elki.data.model
NonNumericFeaturesException
          An exception to signal the encounter of non numeric features where numeric features have been expected.
Normalization
          Normalization performs a normalization on a set of feature vectors and is capable to transform a set of feature vectors to the original attribute ranges.
 

Classes in de.lmu.ifi.dbs.elki.datasource.filter used by de.lmu.ifi.dbs.elki.datasource
ObjectFilter
          Object filters as part of the input step.
 

Classes in de.lmu.ifi.dbs.elki.datasource.filter used by de.lmu.ifi.dbs.elki.datasource.filter
AbstractConversionFilter
          Abstract base class for simple conversion filters such as normalizations and projections.
AbstractFeatureSelectionFilter
           A ProjectionParser projects the objects of its base parser onto a subspace specified by a BitSet.
AbstractFeatureSelectionFilter.Parameterizer
          Parameterization class.
AbstractNormalization
          Abstract super class for all normalizations.
AbstractRandomFeatureSelectionFilter
           A RandomProjectionParser selects a subset of attributes randomly for projection of a ParsingResult.
AbstractRandomFeatureSelectionFilter.Parameterizer
          Parameterization class.
AttributeWiseMinMaxNormalization
          Class to perform and undo a normalization on real vectors with respect to given minimum and maximum in each dimension.
AttributeWiseVarianceNormalization
          Class to perform and undo a normalization on real vectors with respect to given mean and standard deviation in each dimension.
DoubleVectorProjectionFilter
          Parser to project the ParsingResult obtained by a suitable base parser onto a selected subset of attributes.
DoubleVectorRandomProjectionFilter
           Parser to project the ParsingResult obtained by a suitable base parser onto a randomly selected subset of attributes.
InverseDocumentFrequencyNormalization
          Normalization for text frequency vectors, using the inverse document frequency.
NonNumericFeaturesException
          An exception to signal the encounter of non numeric features where numeric features have been expected.
Normalization
          Normalization performs a normalization on a set of feature vectors and is capable to transform a set of feature vectors to the original attribute ranges.
ObjectFilter
          Object filters as part of the input step.
SparseFloatVectorProjectionFilter
           Parser to project the ParsingResult obtained by a suitable base parser onto a selected subset of attributes.
SparseFloatVectorRandomProjectionFilter
          Parser to project the ParsingResult obtained by a suitable base parser onto a randomly selected subset of attributes.
SplitNumberVectorFilter
          Split an existing column into two types.
 


Release 0.4.0 (2011-09-20_1324)