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Quantifying The Impact of Learning Algorithm Parameter Tuning by deAug is a document available to read on EtoBox.

What is Quantifying The Impact of Learning Algorithm Parameter Tuning about?

A systematic comparison has been performed between four induction algorithms on eight data sets. The results indicate that parameter tuning is often more important than the choice of algorithm. The study provides quantitative support to the assertion that some algorithms are more robust than others with respect to parameter configuration.

Author
deAug
Language
EN

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