About:
ELKI is a framework for implementing data-mining algorithms with support for index structures, that includes a wide variety of clustering and outlier detection methods.
Changes:
Additions and improvements from ELKI 0.7.0 to 0.7.1:
Algorithm additions:
GriDBSCAN: DBSCAN using grid partitioning (Minkowski distances only)
Compare-Means and Sort-Means k-means variations (much faster than traditional k-means)
Visualization of dendrograms.
Important bug fixes:
Classes with no package ("default package") would cause errors.
The fast power function implementation was sometimes returning incorrect results.
Random sampling was sometimes not sampling from the full data set.
UI improvements:
The file input source will now automatically choose the Arff parser for .arff files.
MiniGUI now allows choosing other applications.
MiniGUI now displays the command line in a separate field.
MiniGUI displays an error message, if an incorrect classpath or JAyatana (on Ubuntu) is detected.
Export to png now works, we added a work-around for an open Batik bug.
Smaller changes:
Many smaller bug fixes.
C-Index for cluster evaluation now can process larger data sets.
OPTICS output of undefined reachability fixed.
External distance matrixes are easier to use and perform additional checks.
Precomputed distance matrixes can answer range and kNN queries.
Voronoi visualization can be switched in the menu now.
Improved backwards command line compatibility with additional aliases.
Added generated @since annotations in JavaDoc.
Many new unit tests, renamed to the Java conventions.
Low-level reading of service files, to have faster startup.
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