Please use this identifier to cite or link to this item:
http://hdl.handle.net/10174/20668
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| Title: | Age and Gender Identification using Stacking for Classification⋆ Notebook for PAN at CLEF 2016 |
| Authors: | Agrawal, Madhulika
Gonçalves, Teresa |
| Issue Date: | Sep-2016 |
| Publisher: | CEUR |
| Citation: | Madhulika Agrawal and Teresa Gon ̧calves. Age and gender identification using stacking for classification. In Krisztian Balog, Linda Cappellato, Ni- cola Ferro, and Craig Macdonald, editors, Working Notes of CLEF’2016 – Conference and Labs of the Evaluation forum, Évora, Portugal, 5-8 September, 2016., volume 1609, pages 785–790, Évora, PT, September 2016. CEUR |
| Abstract: | This paper presents our approach of identifying the profile of an unknown user based on the activities of known users. The aim of author profiling task of PAN@CLEF 2016 is cross-genre identification of the gender and age of an unknown user. This means training the system using the behavior of different users from one social media platform and identifying the profile of other user on some different platform. Instead of using single classifier to build the system we used a combination of different classifiers, also known as stacking. This approach allowed us explore the strength of all the classifiers and minimize the bias or error enforced by a single classifier. |
| URI: | http://hdl.handle.net/10174/20668 |
| Type: | article |
| Appears in Collections: | INF - Artigos em Livros de Actas/Proceedings
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