Learning to classify with missing and corrupted features
نویسندگان
چکیده
منابع مشابه
Learning with Missing Features
We introduce new online and batch algorithms that are robust to data with missing features, a situation that arises in many practical applications. In the online setup, we allow for the comparison hypothesis to change as a function of the subset of features that is observed on any given round, extending the standard setting where the comparison hypothesis is fixed throughout. In the batch setup...
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ژورنال
عنوان ژورنال: Machine Learning
سال: 2009
ISSN: 0885-6125,1573-0565
DOI: 10.1007/s10994-009-5124-8