Robust methods for data reduction / Alessio Farcomeni and Luca Greco.
Material type:
- 9781466590625
- 000SA.13 23 F221
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Books | ISI Library, Kolkata | 000SA.13 F221 (Browse shelf(Opens below)) | Available | 137121 |
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000SA.12 Si571 Nonparametric statistics for the behavioural sciences | 000SA.12=4 R215 Statistique non parametric asymptotique | 000SA.13 D229 Robust response surfaces, regression, and positive data analyses / | 000SA.13 F221 Robust methods for data reduction / | 000SA.13 J95 Methodology in robust and nonparametric statistics / | 000SA.13 Sh554 Robust correlation : theory and applications / | 000SA.14 K64 Handbook of survival analysis / |
Includes bibliographical references and index.
Section 1. Dimension reduction --
1. Introduction and overview --
2. Multivariate estimation methods --
3. Principal component analysis --
4. Sparse Robust PCA --
5. Canonical correlation analysis --
6. Factor analysis --
Section 2. Sample reduction --
7. k-means and model-based clustering --
8. Robust clustering --
9. Robust model-based clustering --
10. Double clustering --
11. Discriminant analysis.
Robust Methods for Data Reduction gives a non-technical overview of robust data reduction techniques, encouraging the use of these important and useful methods in practical applications. The main areas covered include principal components analysis, sparse principal component analysis, canonical correlation analysis, factor analysis, clustering, double clustering, and discriminant analysis.The first part of the book illustrates how dimension reduction techniques synthesize available information by reducing the dimensionality of the data. The second part focuses on cluster and discriminant analy.
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