| 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 |
Clustering algorithms.
|
| de.lmu.ifi.dbs.elki.algorithm.clustering.correlation |
Correlation clustering algorithms
|
| de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan |
Generalized DBSCAN.
|
| de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical | |
| de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans |
K-means clustering and variations.
|
| 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.clustering.trivial |
Trivial clustering algorithms: all in one, no clusters, label clusterings
These methods are mostly useful for providing a reference result in evaluation.
|
| de.lmu.ifi.dbs.elki.algorithm.outlier.subspace |
Subspace outlier detection methods.
|
| de.lmu.ifi.dbs.elki.algorithm.outlier.trivial |
Trivial outlier detection algorithms: no outliers, all outliers, label outliers.
|
| 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.data.synthetic.bymodel |
Generator using a distribution model specified in an XML configuration file.
|
| de.lmu.ifi.dbs.elki.data.type |
Data type information, also used for type restrictions.
|
| de.lmu.ifi.dbs.elki.evaluation.outlier |
Evaluate an outlier score using a misclassification based cost model.
|
| de.lmu.ifi.dbs.elki.result |
Result types, representation and handling
|
| de.lmu.ifi.dbs.elki.result.textwriter |
Text serialization (CSV, Gnuplot, Console, ...)
|
| de.lmu.ifi.dbs.elki.visualization |
Visualization package of ELKI.
|
| de.lmu.ifi.dbs.elki.visualization.opticsplot |
Code for drawing OPTICS plots
|
| de.lmu.ifi.dbs.elki.visualization.visualizers.optics |
Visualizers that do work on OPTICS plots
|
| de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.cluster |
Visualizers for clustering results based on parallel coordinates.
|
| de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster |
Visualizers for clustering results based on 2D projections.
|
| de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj |
Visualizers that do not use a particular projection.
|
| tutorial.clustering |
Classes from the tutorial on implementing a custom k-means variation.
|
| Class and Description |
|---|
| CorrelationAnalysisSolution
A solution of correlation analysis is a matrix of equations describing the
dependencies.
|
| Class and Description |
|---|
| ClusterModel
Generic cluster model.
|
| EMModel
Cluster model of an EM cluster, providing a mean and a full covariance
Matrix.
|
| MeanModel
Cluster model that stores a mean for the cluster.
|
| Model
Base interface for Model classes.
|
| OPTICSModel
Model for an OPTICS cluster
|
| Class and Description |
|---|
| CorrelationModel
Cluster model using a filtered PCA result and an centroid.
|
| Model
Base interface for Model classes.
|
| Class and Description |
|---|
| Model
Base interface for Model classes.
|
| Class and Description |
|---|
| DendrogramModel
Model for dendrograms, provides the distance to the child cluster.
|
| Class and Description |
|---|
| KMeansModel
Trivial subclass of the
MeanModel that indicates the clustering to be
produced by k-means (so the Voronoi cell visualization is sensible). |
| MeanModel
Cluster model that stores a mean for the cluster.
|
| MedoidModel
Cluster model that stores a mean for the cluster.
|
| Class and Description |
|---|
| Model
Base interface for Model classes.
|
| SubspaceModel
Model for Subspace Clusters.
|
| Class and Description |
|---|
| Model
Base interface for Model classes.
|
| Class and Description |
|---|
| SubspaceModel
Model for Subspace Clusters.
|
| Class and Description |
|---|
| Model
Base interface for Model classes.
|
| Class and Description |
|---|
| Model
Base interface for Model classes.
|
| Class and Description |
|---|
| BaseModel
Abstract base class for Cluster Models.
|
| Bicluster
Wrapper class to provide the basic properties of a bicluster.
|
| ClusterModel
Generic cluster model.
|
| MeanModel
Cluster model that stores a mean for the cluster.
|
| Model
Base interface for Model classes.
|
| Class and Description |
|---|
| Model
Base interface for Model classes.
|
| Class and Description |
|---|
| Model
Base interface for Model classes.
|
| Class and Description |
|---|
| Model
Base interface for Model classes.
|
| Class and Description |
|---|
| Model
Base interface for Model classes.
|
| Class and Description |
|---|
| Model
Base interface for Model classes.
|
| Class and Description |
|---|
| Model
Base interface for Model classes.
|
| Class and Description |
|---|
| Model
Base interface for Model classes.
|
| Class and Description |
|---|
| OPTICSModel
Model for an OPTICS cluster
|
| Class and Description |
|---|
| MeanModel
Cluster model that stores a mean for the cluster.
|
| Model
Base interface for Model classes.
|
| Class and Description |
|---|
| EMModel
Cluster model of an EM cluster, providing a mean and a full covariance
Matrix.
|
| MeanModel
Cluster model that stores a mean for the cluster.
|
| Model
Base interface for Model classes.
|
| Class and Description |
|---|
| Model
Base interface for Model classes.
|
| Class and Description |
|---|
| MeanModel
Cluster model that stores a mean for the cluster.
|