deb_control_files:
- control
- md5sums
deb_fields:
Architecture: all
Depends: default-jre (>= 2:1.8), libbatik-java (>= 1.10), libtrove3-java, libxmlgraphics-commons-java,
libsvm3-java
Description: |-
Data mining algorithm development framework
ELKI: "Environment for Developing KDD-Applications Supported by
Index-Structures" is a development framework for data mining algorithms
written in Java. It includes a large variety of popular data mining
algorithms, distance functions and index structures.
.
Its focus is particularly on clustering and outlier detection methods, in
contrast to many other data mining toolkits that focus on classification.
Additionally, it includes support for index structures to improve algorithm
performance such as R*-Tree and M-Tree.
.
The modular architecture is meant to allow adding custom components such
as distance functions or algorithms, while being able to reuse the other
parts for evaluation.
.
This package contains the compiled ELKI version, and launcher scripts.
Homepage: https://elki-project.github.io/
Installed-Size: '4745'
Maintainer: Erich Schubert <erich@debian.org>
Package: elki
Priority: optional
Section: science
Suggests: elki-dev, libfop-java
Version: 0.7.1-10.1
srcpkg_name: elki
srcpkg_version: 0.7.1-10.1