Generating classifier outputs of fixed accuracy and diversity
نویسندگان
چکیده
We offer an algorithm for random generation of classifier outputs with specified individual accuracies and pairwise dependencies. The outputs are binary vectors (correct/incorrect classification) for a hypothetical data set. The generated team output can be used to study the majority vote over multiple dependent classifiers. 2002 Elsevier Science B.V. All rights reserved.
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ورودعنوان ژورنال:
- Pattern Recognition Letters
دوره 23 شماره
صفحات -
تاریخ انتشار 2002