ICA-Based Binary Feature Construction | Zendy

Ata Kabán | Zendy; Ella Bingham | Zendy

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ICA-Based Binary Feature Construction

Author(s) -

Ata Kabán,

Ella Bingham

Publication year - 2006

Publication title -

lecture notes in computer science

Language(s) - English

Resource type - Book series

SCImago Journal Rank - 0.249

H-Index - 400

eISSN - 1611-3349

pISSN - 0302-9743

ISBN - 3-540-32630-8

DOI - 10.1007/11679363_18

Subject(s) - computer science , binary number , bernoulli's principle , feature (linguistics) , bernoulli distribution , binary data , pattern recognition (psychology) , artificial intelligence , independent component analysis , multivariate statistics , data mining , algorithm , machine learning , random variable , mathematics , statistics , linguistics , philosophy , arithmetic , engineering , aerospace engineering

We address the problem of interactive feature construction and denoising of binary data. To this end, we develop a variational ICA method, employing a multivariate Bernoulli likelihood and independent Beta source densities. We relate this to other binary data models, demonstrating its advantages in two application domains.

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