Adaptive mixture discriminant analysis for supervised learning with unobserved classes
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Publication:288891
DOI10.1007/s00357-014-9147-xzbMath1360.62315OpenAlexW2070305658MaRDI QIDQ288891
Publication date: 27 May 2016
Published in: Journal of Classification (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s00357-014-9147-x
adaptive learningmodel-based classificationsupervised classificationsocial network analysismulticlass novelty detectionunobserved classes
Classification and discrimination; cluster analysis (statistical aspects) (62H30) Social networks; opinion dynamics (91D30) Detection theory in information and communication theory (94A13)
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Cites Work
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- Novelty detection: a review. I. Statistical approaches
- Novelty detection: a review. II. Neural network based approaches
- High-dimensional data clustering
- Self-organization and associative memory.
- Estimating the dimension of a model
- Model-based clustering with noise: Bayesian inference and estimation
- Iterative Reclassification Procedure for Constructing an Asymptotically Optimal Rule of Allocation in Discriminant Analysis
- Normal Discrimination with Unclassified Observations
- Model-Based Gaussian and Non-Gaussian Clustering
- Regularized Gaussian Discriminant Analysis Through Eigenvalue Decomposition
- Latent Space Approaches to Social Network Analysis
- High-Dimensional Discriminant Analysis
- On optimum recognition error and reject tradeoff
- The Nearest Neighbor Classification Rule with a Reject Option
- A new look at the statistical model identification
