The aspect Bernoulli model: multiple causes of presences and absences

DOI10.1007/S10044-007-0096-4zbMath1422.68204DBLPjournals/paa/BinghamKF09OpenAlexW2170183124WikidataQ57743701 ScholiaQ57743701MaRDI QIDQ710618

Ata Kabán, Ella Bingham, Mikael Fortelius

Publication date: 19 October 2010

Published in: PAA. Pattern Analysis and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10044-007-0096-4

zbMATH Keywords

data mining0-1 datamultiple cause modelsprobabilistic latent variable models

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (4)

A Nonlinear Matrix Decomposition for Mining the Zeros of Sparse Data ⋮ Bayesian mean-parameterized nonnegative binary matrix factorization ⋮ Discrete Sparse Coding ⋮ From Binary NMF to Variational Bayes NMF: A Probabilistic Approach

Uses Software

• FastICA

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Asymptotic theory for common principal component analysis
• Predictive modelling of heterogeneous sequence collections by topographic ordering of histories
• Probabilistic Principal Component Analysis
• Non-uniqueness in probabilistic numerical identification of bacteria
• 10.1162/153244303322533214
• 10.1162/jmlr.2003.3.4-5.993
• Learning the parts of objects by non-negative matrix factorization
• Independent Component Analysis and Blind Signal Separation
• Unsupervised learning by probabilistic latent semantic analysis

This page was built for publication: The aspect Bernoulli model: multiple causes of presences and absences