Theory and Algorithms for Shapelet-Based Multiple-Instance Learning
نویسندگان
چکیده
منابع مشابه
Multiple Instance Learning: Algorithms and Applications
Traditional supervised learning requires a training data set that consists of inputs and corresponding labels. In many applications, however, it is difficult or even impossible to accurately and consistently assign labels to inputs. A relatively new learning paradigm called Multiple Instance Learning allows the training of a classifier from ambiguously labeled data. This paradigm has been recei...
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ژورنال
عنوان ژورنال: Neural Computation
سال: 2020
ISSN: 0899-7667,1530-888X
DOI: 10.1162/neco_a_01297