Package | Description |
---|---|
de.lmu.ifi.dbs.elki.algorithm |
Algorithms suitable as a task for the
KDDTask main routine. |
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation |
Correlation clustering algorithms
|
de.lmu.ifi.dbs.elki.algorithm.clustering.optics |
OPTICS family of clustering algorithms.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.subspace |
Axis-parallel subspace clustering algorithms
The clustering algorithms in this package are instances of both, projected clustering algorithms or
subspace clustering algorithms according to the classical but somewhat obsolete classification schema
of clustering algorithms for axis-parallel subspaces.
|
de.lmu.ifi.dbs.elki.algorithm.outlier.subspace |
Subspace outlier detection methods.
|
de.lmu.ifi.dbs.elki.algorithm.statistics |
Statistical analysis algorithms
The algorithms in this package perform statistical analysis of the data
(e.g. compute distributions, distance distributions etc.)
|
de.lmu.ifi.dbs.elki.data |
Basic classes for different data types, database object types and label types.
|
de.lmu.ifi.dbs.elki.data.model |
Cluster models classes for various algorithms.
|
de.lmu.ifi.dbs.elki.evaluation.classification |
Evaluation of classification algorithms.
|
de.lmu.ifi.dbs.elki.evaluation.clustering |
Evaluation of clustering results.
|
de.lmu.ifi.dbs.elki.evaluation.outlier |
Evaluate an outlier score using a misclassification based cost model.
|
de.lmu.ifi.dbs.elki.math.geometry |
Algorithms from computational geometry.
|
de.lmu.ifi.dbs.elki.result |
Result types, representation and handling
|
de.lmu.ifi.dbs.elki.result.textwriter.writers |
Serialization handlers for individual data types.
|
Modifier and Type | Class and Description |
---|---|
static class |
MaterializeDistances.DistanceEntry
Object representing a pairwise distance.
|
Modifier and Type | Class and Description |
---|---|
static class |
HiCO.HiCOClusterOrderEntry
Cluster order entry for HiCO.
|
Modifier and Type | Class and Description |
---|---|
class |
CorrelationClusterOrderEntry<SELF extends CorrelationClusterOrderEntry<SELF>>
Cluster order entry for correlation-based OPTICS variants.
|
class |
DoubleDistanceClusterOrderEntry
Entry in a
ClusterOrderResult . |
Modifier and Type | Class and Description |
---|---|
static class |
DiSH.DiSHClusterOrderEntry
Cluster order entry for DiSH.
|
static class |
HiSC.HiSCClusterOrderEntry
Cluster order entry for HiSC.
|
Modifier and Type | Class and Description |
---|---|
static class |
SOD.SODModel
SOD Model class
|
Modifier and Type | Class and Description |
---|---|
static class |
MeanAveragePrecisionForDistance.MAPResult
Result object for MAP scores.
|
Modifier and Type | Class and Description |
---|---|
class |
Cluster<M extends Model>
Generic cluster class, that may or not have hierarchical information.
|
Modifier and Type | Class and Description |
---|---|
class |
CorrelationAnalysisSolution<V extends NumberVector>
A solution of correlation analysis is a matrix of equations describing the
dependencies.
|
class |
CorrelationModel<V extends FeatureVector<?>>
Cluster model using a filtered PCA result and an centroid.
|
class |
DimensionModel
Cluster model just providing a cluster dimensionality.
|
class |
EMModel
Cluster model of an EM cluster, providing a mean and a full covariance
Matrix.
|
class |
KMeansModel
Trivial subclass of the
MeanModel that indicates the clustering to be
produced by k-means (so the Voronoi cell visualization is sensible). |
class |
LinearEquationModel
Cluster model containing a linear equation system for the cluster.
|
class |
MeanModel
Cluster model that stores a mean for the cluster.
|
class |
MedoidModel
Cluster model that stores a mean for the cluster.
|
class |
PrototypeModel<V>
Cluster model that stores a prototype for each cluster.
|
class |
SubspaceModel
Model for Subspace Clusters.
|
Modifier and Type | Class and Description |
---|---|
class |
ConfusionMatrixEvaluationResult
Provides the prediction performance measures for a classifier based on the
confusion matrix.
|
Modifier and Type | Class and Description |
---|---|
static class |
EvaluateClustering.ScoreResult
Result object for outlier score judgements.
|
Modifier and Type | Class and Description |
---|---|
static class |
OutlierPrecisionAtKCurve.PrecisionAtKCurve
Precision at K curve.
|
static class |
OutlierPrecisionRecallCurve.PRCurve
P/R Curve
|
static class |
OutlierROCCurve.ROCResult
Result object for ROC curves.
|
static class |
OutlierSmROCCurve.SmROCResult
Result object for Smooth ROC curves.
|
Modifier and Type | Class and Description |
---|---|
class |
XYCurve
An XYCurve is an ordered collection of 2d points, meant for chart generation.
|
Modifier and Type | Class and Description |
---|---|
class |
AprioriResult
Result class for Apriori Algorithm.
|
class |
EvaluationResult
Abstract evaluation result.
|
Modifier and Type | Method and Description |
---|---|
void |
TextWriterTextWriteable.write(TextWriterStream out,
String label,
TextWriteable obj)
Use the objects own text serialization.
|
Copyright © 2014 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.