Package | Description |
---|---|
de.lmu.ifi.dbs.elki.datasource |
Data normalization (and reconstitution) of data sets.
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de.lmu.ifi.dbs.elki.datasource.filter |
Data filtering, in particular for normalization and projection.
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de.lmu.ifi.dbs.elki.datasource.filter.normalization |
Data normalization.
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de.lmu.ifi.dbs.elki.datasource.filter.transform |
Data space transformations.
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Modifier and Type | Field and Description |
---|---|
protected List<ObjectFilter> |
AbstractDatabaseConnection.filters
The filters to invoke
|
protected List<ObjectFilter> |
AbstractDatabaseConnection.Parameterizer.filters
Filters
|
Modifier and Type | Interface and Description |
---|---|
interface |
StreamFilter
Streaming filters are often more efficient (less memory use) and can be used
in more settings.
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractConversionFilter<I,O>
Abstract base class for simple conversion filters such as normalizations and projections.
|
class |
AbstractStreamConversionFilter<I,O>
Abstract base class for simple conversion filters such as normalizations and
projections.
|
class |
AbstractStreamFilter
Abstract base class for streaming filters.
|
class |
AbstractVectorConversionFilter<I,O extends NumberVector<?>>
Abstract class for filters that produce number vectors.
|
class |
AbstractVectorStreamConversionFilter<I,O extends NumberVector<?>>
Abstract base class for streaming filters that produce vectors.
|
class |
ByLabelFilter
A filter to sort the data set by some label.
|
class |
ClassLabelFilter
Class that turns a label column into a class label column.
|
class |
ClassLabelFromPatternFilter
Streaming filter to derive an outlier class label.
|
class |
DropNaNFilter
A filter to drop all records that contain NaN values.
|
class |
ExternalIDFilter
Class that turns a label column into an external ID column.
|
class |
FixedDBIDsFilter
This filter assigns static DBIDs, based on the sequence the objects appear in
the bundle by adding a column of DBID type to the bundle.
|
class |
HistogramJitterFilter<V extends NumberVector<?>>
Add Jitter, preserving the histogram properties (same sum, nonnegative).
|
class |
NoMissingValuesFilter
A filter to remove entries that have missing values.
|
class |
NoOpFilter
Dummy filter that doesn't do any filtering.
|
class |
RandomSamplingStreamFilter
Subsampling stream filter.
|
class |
ReplaceNaNWithRandomFilter
A filter to replace all NaN values.
|
class |
ShuffleObjectsFilter
A filter to shuffle the dataset.
|
class |
SortByLabelFilter
A filter to sort the data set by some label.
|
class |
SparseVectorFieldFilter<V extends SparseNumberVector<?>>
Class that turns sparse float vectors into a proper vector field, by setting
the maximum dimensionality for each vector.
|
class |
SplitNumberVectorFilter<V extends NumberVector<?>>
Split an existing column into two types.
|
Modifier and Type | Interface and Description |
---|---|
interface |
Normalization<O>
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.
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractNormalization<O extends NumberVector<?>>
Abstract super class for all normalizations.
|
class |
AbstractStreamNormalization<O extends NumberVector<?>>
Abstract super class for all normalizations.
|
class |
AttributeWiseCDFNormalization<V extends NumberVector<?>>
Class to perform and undo a normalization on real vectors by estimating the
distribution of values along each dimension independently, then rescaling
objects to the cumulative density function (CDF) value at the original
coordinate.
|
class |
AttributeWiseErfNormalization<O extends NumberVector<?>>
Attribute-wise Normalization using the error function.
|
class |
AttributeWiseMADNormalization<V extends NumberVector<?>>
Median Absolute Deviation is used for scaling the data set as follows:
First, the median, and median absolute deviation are computed in each axis.
|
class |
AttributeWiseMinMaxNormalization<V extends NumberVector<?>>
Class to perform and undo a normalization on real vectors with respect to
given minimum and maximum in each dimension.
|
class |
AttributeWiseVarianceNormalization<V extends NumberVector<?>>
Class to perform and undo a normalization on real vectors with respect to
given mean and standard deviation in each dimension.
|
class |
InverseDocumentFrequencyNormalization<V extends SparseNumberVector<?>>
Normalization for text frequency vectors, using the inverse document
frequency.
|
class |
LengthNormalization<V extends NumberVector<?>>
Class to perform a normalization on vectors to norm 1.
|
class |
RankTieNormalization
Normalize vectors according to their rank in the attributes.
|
class |
TFIDFNormalization<V extends SparseNumberVector<?>>
Perform full TF-IDF Normalization as commonly used in text mining.
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractSupervisedProjectionVectorFilter<V extends NumberVector<?>>
Base class for supervised projection methods.
|
class |
ClassicMultidimensionalScalingTransform<O>
Rescale the data set using multidimensional scaling, MDS.
|
class |
GlobalPrincipalComponentAnalysisTransform<O extends NumberVector<?>>
Apply principal component analysis to the data set.
|
class |
LatLngToECEFFilter<V extends NumberVector<?>>
Project a 2D data set (latitude, longitude) to a 3D coordinate system (X, Y,
Z), such that Euclidean distance is line-of-sight.
|
class |
LinearDiscriminantAnalysisFilter<V extends NumberVector<?>>
Linear Discriminant Analysis (LDA) / Fisher's linear discriminant.
|
class |
LngLatToECEFFilter<V extends NumberVector<?>>
Project a 2D data set (longitude, latitude) to a 3D coordinate system (X, Y,
Z), such that Euclidean distance is line-of-sight.
|
class |
NumberVectorFeatureSelectionFilter<V extends NumberVector<?>>
Parser to project the ParsingResult obtained by a suitable base parser onto a
selected subset of attributes.
|
class |
NumberVectorRandomFeatureSelectionFilter<V extends NumberVector<?>>
Parser to project the ParsingResult obtained by a suitable base parser onto a
randomly selected subset of attributes.
|
class |
ProjectionFilter<I,O>
Apply a projection to the data.
|