Thresholding Strategies for Large Scale Multi-Label Text Classifier - Publikacja - MOST Wiedzy

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Thresholding Strategies for Large Scale Multi-Label Text Classifier

Abstrakt

This article presents an overview of thresholding methods for labeling objects given a list of candidate classes’ scores. These methods are essential to multi-label classification tasks, especially when there are a lot of classes which are organized in a hierarchy. Presented techniques are evaluated using the state-of-the-art dedicated classifier on medium scale text corpora extracted from Wikipedia. Obtained results show that the classification performance can be improved with the use of new class-specific thresholding methods, which set decision values depending on each candidate class separately

Informacje szczegółowe

Kategoria:
Publikacja w czasopiśmie
Typ:
materiały konferencyjne indeksowane w Web of Science
Tytuł wydania:
Human System Interaction (HSI), 2013 The 6th International Conference on strony 350 - 355
Język:
angielski
Rok wydania:
2013
Opis bibliograficzny:
Draszawka K., Szymański J..: Thresholding Strategies for Large Scale Multi-Label Text Classifier, W: Human System Interaction (HSI), 2013 The 6th International Conference on, 2013, IEEE,.
Weryfikacja:
Politechnika Gdańska

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