Abstract:
ABSTRACT: Although many algorithms for learning from examples have been developed and many comparisons have been reported, there is no generally accepted benchmark for classifier learning. The existence of a standard benchmark would greatly assist such comparisons. Sixteen dimensions are proposed to describe classification tasks. Based on these, thirteen real-world and synthetic datasets are chosen by a set covering method from the UCI Repository of machine learning databases to form such a benchmark. 1.
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