Abstract
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
Citations
-
1 1
CrossRef
-
0
Web of Science
-
1 4
Scopus
Authors (2)
Cite as
Full text
full text is not available in portal
Keywords
Details
- Category:
- Conference activity
- Type:
- materiały konferencyjne indeksowane w Web of Science
- Title of issue:
- Human System Interaction (HSI), 2013 The 6th International Conference on strony 350 - 355
- Language:
- English
- Publication year:
- 2013
- Bibliographic description:
- 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,.
- DOI:
- Digital Object Identifier (open in new tab) 10.1109/hsi.2013.6577846
- Verified by:
- Gdańsk University of Technology
seen 134 times
Recommended for you
Segmentation-Based BI-RADS ensemble classification of breast tumours in ultrasound images
- M. Bobowicz,
- M. Badocha,
- K. Gwozdziewicz
- + 4 authors