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|Volltext||1.pdf (283 KB)|
|URN (für Zitat)||http://nbn-resolving.org/urn:nbn:de:swb:90-AAA397944|
|Titel||PROBEN 1 - a set of benchmarks and benchmarking rules for neural network training algorithms.|
|Institution||Fakultät für Informatik (INFORMATIK)
Institut für Programmstrukturen und Datenorganisation (IPD)
|Erscheinungsvermerk||Karlsruhe 1994. (Technical report. Fakultät für Informatik, Universität Karlsruhe. 1994,21.)|
Proben1 is a collection of problems for neural network learning in
the realm of pattern classification and function approximation
plus a set of rules and conventions for carrying out benchmark
tests with these or similar problems. Proben1 contains 15 data
sets from 12 different domains. All datasets represent realistic
problems which could be called diagnosis tasks and all but one
consist of real world data. The datasets are all presented in the
same simple format, using an attribute representation that can
directly be used for neural network training.
Along with the datasets, Proben1 defines a set of rules for how to
conduct and how to document neural network benchmarking.
The purpose of the problem and rule collection is to give
researchers easy access to data for the evaluation of their
algorithms and networks and to make direct comparison of the
published results feasible.
This report describes the datasets and the benchmarking rules. It
also gives some basic performance measures indicating the
difficulty of the various problems. These measures can be used as
baselines for comparison.