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The summer before the book's publication, Little, Brown sent promotional materials — an excerpt of the King Alfred Plan alongside details of the book's publication, all in a manila folder labelled "CLASSIFICATION: TOP SECRET" — to two thousand booksellers and jobbers.
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Also, our approach is applicable to single-label classification, multi-label classification, as well as regression problems.
Apparently, this is a shortcoming of the binary classification itself, as opposed to multi-label classification.
Kernel extreme learning machine was applied to multi-label classification problem (ML-KELM) in this paper, so the iterative learning operations can be avoided.
Multi-label classification requires different evaluation measures than traditional single-label classification.
Binary relevance corresponds to the baseline of multi-label classification.
Single-label classification and regression cannot model this multiplicity.
This way, CLR manages to perform multi-label classification.
They transform the multi-label classification task into one or more single-label classification, regression, or ranking tasks.
Past approaches towards automated detection of emotions in music modeled the learning problem as a single-label classification [3, 4] regression [5], or multi-label classification [6 9] task.
In the multi-label classification experiment, each node is assigned to one or more class labels.
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