An Error Bound Based on a Worst Likely Assignment
نویسندگان
چکیده
This paper introduces a new PAC transductive error bound for classification. The method uses information from the training examples and inputs of working examples to develop a set of likely assignments to outputs of the working examples. A likely assignment with maximum error determines the bound. The method is very effective for small data sets.
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عنوان ژورنال:
- Journal of Machine Learning Research
دوره 9 شماره
صفحات -
تاریخ انتشار 2008