Package | Description |
---|---|
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.
|
de.lmu.ifi.dbs.elki.datasource.filter.cleaning |
Filters for data cleaning.
|
de.lmu.ifi.dbs.elki.datasource.filter.normalization |
Data normalization.
|
de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise |
Normalizations operating on columns / variates; where each column is treated independently.
|
de.lmu.ifi.dbs.elki.datasource.filter.normalization.instancewise |
Instancewise normalization, where each instance is normalized independently.
|
de.lmu.ifi.dbs.elki.datasource.filter.selection |
Filters for selecting and sorting data to process.
|
de.lmu.ifi.dbs.elki.datasource.filter.transform |
Data space transformations.
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de.lmu.ifi.dbs.elki.datasource.filter.typeconversions |
Filters to perform data type conversions.
|
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) as they do not
keep a reference to earlier data.
|
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 |
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 |
NoOpFilter
Dummy filter that doesn't do any filtering.
|
Modifier and Type | Class and Description |
---|---|
class |
DropNaNFilter
A filter to drop all records that contain NaN values.
|
class |
NoMissingValuesFilter
A filter to remove entries that have missing values.
|
class |
ReplaceNaNWithRandomFilter
A filter to replace all NaN values.
|
class |
VectorDimensionalityFilter<V extends NumberVector>
Filter to remove all vectors that do not have the desired dimensionality.
|
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<V extends NumberVector>
Abstract super class for all normalizations.
|
class |
AbstractStreamNormalization<V extends NumberVector>
Abstract super class for all normalizations.
|
Modifier and Type | Class and Description |
---|---|
class |
AttributeWiseBetaNormalization<V extends NumberVector>
Project the data using a Beta distribution.
|
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<V 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 |
AttributeWiseMeanNormalization<V extends NumberVector>
Normalization designed for data with a meaningful zero: Each
attribute is scaled to have the same mean (but 0 is not changed).
|
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 |
IntegerRankTieNormalization
Normalize vectors according to their rank in the attributes.
|
class |
InverseDocumentFrequencyNormalization<V extends SparseNumberVector>
Normalization for text frequency (TF) vectors, using the inverse document
frequency (IDF).
|
Modifier and Type | Class and Description |
---|---|
class |
HellingerHistogramNormalization<V extends NumberVector>
Normalize histograms by scaling them to L1 norm 1, then taking the square
root in each attribute.
|
class |
InstanceLogRankNormalization<V extends NumberVector>
Normalize vectors such that the smallest value of each instance is 0, the
largest is 1, but using log_2(1+x).
|
class |
InstanceMeanVarianceNormalization<V extends NumberVector>
Normalize vectors such that they have zero mean and unit variance.
|
class |
InstanceMinMaxNormalization<V extends NumberVector>
Normalize vectors such that the smallest attribute is 0, the largest is 1.
|
class |
InstanceRankNormalization<V extends NumberVector>
Normalize vectors such that the smallest value of each instance is 0, the
largest is 1.
|
class |
LengthNormalization<V extends NumberVector>
Class to perform a normalization on vectors to norm 1.
|
class |
Log1PlusNormalization<V extends NumberVector>
Normalize the data set by applying log(1+|x|*b)/log(b+1) to any value.
|
Modifier and Type | Class and Description |
---|---|
class |
ByLabelFilter
A filter to select data set by their label.
|
class |
RandomSamplingStreamFilter
Subsampling stream filter.
|
class |
ShuffleObjectsFilter
A filter to shuffle the dataset.
|
class |
SortByLabelFilter
A filter to sort the data set by some label.
|
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 |
FastMultidimensionalScalingTransform<O>
Rescale the data set using multidimensional scaling, MDS.
|
class |
GlobalPrincipalComponentAnalysisTransform<O extends NumberVector>
Apply principal component analysis to the data set.
|
class |
HistogramJitterFilter<V extends NumberVector>
Add Jitter, preserving the histogram properties (same sum, nonnegative).
|
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 |
PerturbationFilter<V extends NumberVector>
A filter to perturb the values by adding micro-noise.
|
class |
ProjectionFilter<I,O>
Apply a projection to the data.
|
Modifier and Type | Class and Description |
---|---|
class |
ClassLabelFilter
Class that turns a label column into a class label column.
|
class |
ClassLabelFromPatternFilter
Streaming filter to derive an outlier class label.
|
class |
ExternalIDFilter
Class that turns a label column into an external ID column.
|
class |
MultivariateTimeSeriesFilter<V extends FeatureVector<?>>
Class to "fold" a flat number vector into a multivariate time series.
|
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.
|
class |
UncertainifyFilter<UO extends UncertainObject>
Filter class to transform a database containing vector fields (TODO I need to
express this more correctly) into a database containing
UncertainObject fields. |
class |
UncertainSplitFilter
Filter to transform a single vector into a set of samples to interpret as
uncertain observation.
|
class |
WeightedUncertainSplitFilter
Filter to transform a single vector into a set of samples and weights to
interpret as uncertain observation.
|
Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.