Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
New Algorithms for Learning of Mixture Models and Their Application for Classification and Density Estimation

New Algorithms for Learning of Mixture Models and Their Application for Classification and Density Estimation

Iswanto, Bambang Heru

Paperback

General Computers

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ISBN10: 3832508090
ISBN13: 9783832508098
Publisher: Logos Verlag Berlin
Published: Jan 31 2005
Pages: 150
Weight: 1.20
Height: 0.40 Width: 6.55 Depth: 9.46
Language: English
Mixture model is known as a convenient way for modelling the probability density function in statistics. Recently, the method is adopted by machine learning communities in a variety of application settings such as cluster analysis, classification, density estimation and function approximation. This book concerns with learning algorithms of the mixture models for density estimation and classification tasks. Special attention is given for the semi-supervised learning and active learning methods which are very important in many practical settings. The presented learning methods attempt to reduce the size of labelled data sets required to achieve certain level of classification performance.

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