Improved expectation maximization algorithm for Gaussian mixed model using the kernel method
Fraud activities have contributed to heavy losses suffered by telecommunication companies. In this paper, we attempt to use Gaussian mixed model, which is a probabilistic model normally used in speech recognition to identify fraud calls in the telecommunication industry. We look at several issues en...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Hindawi Publishing Corporation
2013
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| Online Access: | http://psasir.upm.edu.my/id/eprint/30397/ http://psasir.upm.edu.my/id/eprint/30397/1/Improved%20expectation%20maximization%20algorithm%20for%20Gaussian%20mixed%20model%20using%20the%20kernel%20method.pdf |
| _version_ | 1848846664909979648 |
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| author | Mohd Yusoff, Mohd Izhan Mohamed, Ibrahim Abu Bakar, Mohd Rizam |
| author_facet | Mohd Yusoff, Mohd Izhan Mohamed, Ibrahim Abu Bakar, Mohd Rizam |
| author_sort | Mohd Yusoff, Mohd Izhan |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Fraud activities have contributed to heavy losses suffered by telecommunication companies. In this paper, we attempt to use Gaussian mixed model, which is a probabilistic model normally used in speech recognition to identify fraud calls in the telecommunication industry. We look at several issues encountered when calculating the maximum likelihood estimates of the Gaussian mixed model using an Expectation Maximization algorithm. Firstly, we look at a mechanism for the determination of the initial number of Gaussian components and the choice of the initial values of the algorithm using the kernel method. We show via simulation that the technique improves the performance of the algorithm. Secondly, we developed a procedure for determining the order of the Gaussian mixed model using the log-likelihood function and the Akaike information criteria. Finally, for illustration, we apply the improved algorithm to real telecommunication data. The modified method will pave the way to introduce a comprehensive method for detecting fraud calls in future work. |
| first_indexed | 2025-11-15T09:06:19Z |
| format | Article |
| id | upm-30397 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T09:06:19Z |
| publishDate | 2013 |
| publisher | Hindawi Publishing Corporation |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-303972015-10-08T03:16:19Z http://psasir.upm.edu.my/id/eprint/30397/ Improved expectation maximization algorithm for Gaussian mixed model using the kernel method Mohd Yusoff, Mohd Izhan Mohamed, Ibrahim Abu Bakar, Mohd Rizam Fraud activities have contributed to heavy losses suffered by telecommunication companies. In this paper, we attempt to use Gaussian mixed model, which is a probabilistic model normally used in speech recognition to identify fraud calls in the telecommunication industry. We look at several issues encountered when calculating the maximum likelihood estimates of the Gaussian mixed model using an Expectation Maximization algorithm. Firstly, we look at a mechanism for the determination of the initial number of Gaussian components and the choice of the initial values of the algorithm using the kernel method. We show via simulation that the technique improves the performance of the algorithm. Secondly, we developed a procedure for determining the order of the Gaussian mixed model using the log-likelihood function and the Akaike information criteria. Finally, for illustration, we apply the improved algorithm to real telecommunication data. The modified method will pave the way to introduce a comprehensive method for detecting fraud calls in future work. Hindawi Publishing Corporation 2013 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/30397/1/Improved%20expectation%20maximization%20algorithm%20for%20Gaussian%20mixed%20model%20using%20the%20kernel%20method.pdf Mohd Yusoff, Mohd Izhan and Mohamed, Ibrahim and Abu Bakar, Mohd Rizam (2013) Improved expectation maximization algorithm for Gaussian mixed model using the kernel method. Mathematical Problems in Engineering, 2013. art. no. 757240. pp. 1-9. ISSN 1024-123X http://www.hindawi.com/journals/mpe/2013/757240/ 10.1155/2013/757240 |
| spellingShingle | Mohd Yusoff, Mohd Izhan Mohamed, Ibrahim Abu Bakar, Mohd Rizam Improved expectation maximization algorithm for Gaussian mixed model using the kernel method |
| title | Improved expectation maximization algorithm for Gaussian mixed model using the kernel method |
| title_full | Improved expectation maximization algorithm for Gaussian mixed model using the kernel method |
| title_fullStr | Improved expectation maximization algorithm for Gaussian mixed model using the kernel method |
| title_full_unstemmed | Improved expectation maximization algorithm for Gaussian mixed model using the kernel method |
| title_short | Improved expectation maximization algorithm for Gaussian mixed model using the kernel method |
| title_sort | improved expectation maximization algorithm for gaussian mixed model using the kernel method |
| url | http://psasir.upm.edu.my/id/eprint/30397/ http://psasir.upm.edu.my/id/eprint/30397/ http://psasir.upm.edu.my/id/eprint/30397/ http://psasir.upm.edu.my/id/eprint/30397/1/Improved%20expectation%20maximization%20algorithm%20for%20Gaussian%20mixed%20model%20using%20the%20kernel%20method.pdf |