** Please accept our apologees if you receive this announcement more than
once **
Dear machine learning researchers and practioners,
we would like to introduce YALE (Yet Another Learning Environment) to you:
http://yale.cs.uni-dortmund.de/
YALE is a flexible and modular environment for machine learning experiments
and applications. The experimental setup can be easily described in a
configuration file in a simple XML format and may consist of arbitrarily
nested machine learning and data pre-processing operators and operator
chains. Among others, YALE offers operators for:
* machine learning algorithms for classification, regression, and
clustering including wrappers for a number of external machine learning
programs like support vector machines (SVM^light, mySVM), the decision
tree inducer C4.5, and all learners and clusterers offered by WEKA;
* feature selection and generation: forward selection, backward elimination,
and several genetic algorithms;
* performance evaluation: cross-validation and other evaluation schemes,
several performance criteria for classification and regression, operators
for parameter optimization in enclosed operators or operator chains, and
operators for logging and presenting results;
* in- and output: flexible operators for data in- and output, support of
flexible experimental (re)arrangements, usage of (optional) meta
information on data.
YALE provides an easy to use extension mechanism that makes it possible to
integrate new operators and adapt YALE to your personal requirements. Since
YALE is entirely written in Java, it runs on any major platform/operating
system. YALE is a freely available open source software under the terms of
the GNU General Public Licencse. You are weclome to use it!
Best regards,
Simon Fischer, Ingo Mierswa, Oliver Ritthoff, and Ralf Klinkenberg
+-----------------------------+--------------------------------------------+
| Ralf Klinkenberg | [EMAIL PROTECTED] ___ |
| LS K�nstliche Intelligenz | http://www-ai.cs.uni-dortmund.de //// |
| Fachbereich Informatik VIII | UNI DO// |
| Universit�t Dortmund | Tel.: (+49 231) 755-5103 ___ //// |
| D - 44221 Dortmund | Fax: (+49 231) 755-5105 \\\\/// |
| Germany | B�ro: GB IV / R 117 \\\\/ |
+-----------------------------+--------------------------------------------+
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