What Daimler-benz Has Learned as an Industrial Partner from the Machine Learning Project Statlog
نویسنده
چکیده
Author of this paper was coordinator of the Machine Learning project StatLog during 1990-1993. This project was supported nancially by the European Community. The main aim of StatLog was to evaluate diier-ent learning algorithms using real industrial and commercial applications. As an industrial partner and contributor, Daimler-Benz has introduced diierent applications to Stat-Log among them fault diagnosis, letter and digit recognition, credit-scoring and prediction of the number of registered trucks. We have learned a lot of lessons from this project which have eeected our application oriented research in the eld of Machine Learning (ML) in Daimler-Benz. We have distinguished that, especially, more research is necessary to prepare the ML-algorithms to handle the real industrial and commercial applications. In this paper we describe, shortly, the Daimler-Benz applications in StatLog, we discuss shortcomings of the applied ML-algorithms and nally we outline the elds where we think further research is necessary.
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