Formulizing Co-Clusters &Selection Methods Based On SVD in Data Mining
Language: English
Published by LAP LAMBERT Academic Publishing Sep 2018, 2018
- Softcover
- New
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
AbeBooks seller since January 11, 2012
Condition: New
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This item is printed on demand - it takes 3-4 days longer - Neuware -Traditional clustering and feature selection methods consider the data matrix as static. However, the data matrices evolve smoothly over time in many applications. A simple approach to learn from these time-evolving data matrices is to analyze them separately. Such strategy ignores the time-dependent nature of the underlying data. We propose two formulations for evolutionary co-clustering and feature selection based on the fused Lasso regularization. The evolutionary co-clustering formulation is able to identify smoothly varying hidden block structures embedded into the matrices along the temporal dimension. Our formulation is very flexible and allows for imposing smoothness constraints over only one dimension of the data matrices. The evolutionary feature selection formulation can uncover shared features in clustering from time-evolving data matrices. We show that the optimization problems involved are non-convex, non-smooth and non-separable. To compute the solutions efficiently, we develop a two-step procedure that optimizes the objective function iteratively. 68 pp. Englisch. …
Seller Inventory # 9783659716157
- Title
- Formulizing Co-Clusters &Selection Methods Based On SVD in Data Mining
- Author
- D Kishore Babu
- Publisher
- LAP LAMBERT Academic Publishing Sep 2018
- Publication year
- 2018
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 3659716154
- ISBN 13
- 9783659716157
- Item weight
- 119 grams
- Dimensions
- 220x150x5 mm
"Synopsis" may belong to another edition of this title.
BuchWeltWeit Ludwig Meier e.K.
Bergisch Gladbach, Germany
AbeBooks seller since January 11, 2012
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