Selecting the optimal number of components for a Gaussian mixture model
We compare two approaches to determining the optimal number of component Gaussians to include in a Gaussian mixture model, the Akaike information criterion and the Rissanen (1989) minimum description length method.< >
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| creator | McKenzie, P. Alder, M. |
| description | We compare two approaches to determining the optimal number of component Gaussians to include in a Gaussian mixture model, the Akaike information criterion and the Rissanen (1989) minimum description length method.< > |
| doi_str_mv | 10.1109/ISIT.1994.394626 |
| format | Conference Proceeding |
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| identifier | ISBN: 0780320158 |
| ispartof | Proceedings of 1994 IEEE International Symposium on Information Theory, 1994, p.393 |
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| language | eng |
| recordid | cdi_ieee_primary_394626 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Algebra Australia Cost function Gaussian distribution Gaussian processes Information processing Intelligent systems Probability density function Probability distribution Random variables |
| title | Selecting the optimal number of components for a Gaussian mixture model |
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