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Multilabel classification assigns to each sample a set of target labels. This can be thought as predicting properties of a data-point that are not mutually exclusive, such as topics that are relevant for a document. A text might be about any of religion, politics, finance or education at the same time or none of these.

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Python library that can compute the confusion matrix for multi-label classification

Look at sed_eval library. It is developed for evaluating event detection in audio which is a multi-label problem (as in each audio, multiple events exist). They have many evaluation options, which mig …
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