Ensembles of diverse classifiers using synthetic training data
The goal of an ensemble construction with several classifiers is to achieve better generalization than that of a single classifier. And proper diversity among classifiers is considered as the condition for an ensemble construction. This paper investigates synthetic pattern for diversity among class...
| Main Authors: | , , , |
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| Format: | Proceeding Paper |
| Language: | English |
| Published: |
2012
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/24981/ http://irep.iium.edu.my/24981/1/1051C.pdf |
| _version_ | 1848779387592245248 |
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| author | Akhand, M.A.H Shill, P.C. Rahman, M.M. Hafizur Murase, K. |
| author_facet | Akhand, M.A.H Shill, P.C. Rahman, M.M. Hafizur Murase, K. |
| author_sort | Akhand, M.A.H |
| building | IIUM Repository |
| collection | Online Access |
| description | The goal of an ensemble construction with several
classifiers is to achieve better generalization than that of a single classifier. And proper diversity among classifiers is considered as the condition for an ensemble construction. This paper investigates synthetic pattern for diversity among classifiers. It alters input feature values of some patterns with the values of other patterns to get synthetic patterns. The pattern generation from using exiting patterns seems emphasize both accuracy and
diversity among individual classifiers. Ensemble based on the synthetic patterns is evaluated for both neural networks and decision trees on a set of benchmark problems and was found to show good generalization ability. |
| first_indexed | 2025-11-14T15:16:58Z |
| format | Proceeding Paper |
| id | iium-24981 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T15:16:58Z |
| publishDate | 2012 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-249812012-09-18T02:07:16Z http://irep.iium.edu.my/24981/ Ensembles of diverse classifiers using synthetic training data Akhand, M.A.H Shill, P.C. Rahman, M.M. Hafizur Murase, K. TK7885 Computer engineering The goal of an ensemble construction with several classifiers is to achieve better generalization than that of a single classifier. And proper diversity among classifiers is considered as the condition for an ensemble construction. This paper investigates synthetic pattern for diversity among classifiers. It alters input feature values of some patterns with the values of other patterns to get synthetic patterns. The pattern generation from using exiting patterns seems emphasize both accuracy and diversity among individual classifiers. Ensemble based on the synthetic patterns is evaluated for both neural networks and decision trees on a set of benchmark problems and was found to show good generalization ability. 2012-07-03 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/24981/1/1051C.pdf Akhand, M.A.H and Shill, P.C. and Rahman, M.M. Hafizur and Murase, K. (2012) Ensembles of diverse classifiers using synthetic training data. In: International Conference on Computer and Communication Engineering (ICCCE 2012), 3-5 July 2012, Seri Pacific Hotel Kuala Lumpur. |
| spellingShingle | TK7885 Computer engineering Akhand, M.A.H Shill, P.C. Rahman, M.M. Hafizur Murase, K. Ensembles of diverse classifiers using synthetic training data |
| title | Ensembles of diverse classifiers using synthetic training data |
| title_full | Ensembles of diverse classifiers using synthetic training data |
| title_fullStr | Ensembles of diverse classifiers using synthetic training data |
| title_full_unstemmed | Ensembles of diverse classifiers using synthetic training data |
| title_short | Ensembles of diverse classifiers using synthetic training data |
| title_sort | ensembles of diverse classifiers using synthetic training data |
| topic | TK7885 Computer engineering |
| url | http://irep.iium.edu.my/24981/ http://irep.iium.edu.my/24981/1/1051C.pdf |