Classification and Multivariate Analysis for Complex Data Structures [electronic resource] / edited by Bernard Fichet, Domenico Piccolo, Rosanna Verde, Maurizio Vichi.

Contributor(s): Fichet, Bernard [editor.] | Piccolo, Domenico [editor.] | Verde, Rosanna [editor.] | Vichi, Maurizio [editor.] | SpringerLink (Online service)
Material type: TextTextSeries: Studies in Classification, Data Analysis, and Knowledge Organization: Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2011Description: XIX, 473 p. 110 illus., 34 illus. in color. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783642133121Subject(s): Statistics | Data structures (Computer science) | Mathematical statistics | Multimedia information systems | Probabilities | Statistics | Statistical Theory and Methods | Probability and Statistics in Computer Science | Data Structures, Cryptology and Information Theory | Probability Theory and Stochastic Processes | Multimedia Information SystemsAdditional physical formats: Printed edition:: No titleDDC classification: 519.5 LOC classification: QA276-280Online resources: Click here to access online
Contents:
Key Notes -- Classification and Discrimination -- Data Mining -- Robustness and Classification -- Categorical Data and Latent Class Approach -- Latent Variables and Related Methods -- Symbolic, Multivalued and Conceptual Data Analysis -- Spatial, Temporal, Streaming and Functional Data Analysis -- Bio and Health Science.
In: Springer eBooksSummary: The growing capabilities in generating and collecting data has risen an urgent need of new techniques and tools in order to analyze, classify and summarize statistical information, as well as to discover and characterize trends, and to automatically bag anomalies. This volume provides the latest advances in data analysis methods for multidimensional data which can present a complex structure: The book offers a selection of papers presented at the first Joint Meeting of the Société Francophone de Classification and the Classification and Data Analysis Group of the Italian Statistical Society. Special attention is paid to new methodological contributions from both the theoretical and the applicative point of views, in the fields of Clustering, Classification, Time Series Analysis, Multidimensional Data Analysis, Knowledge Discovery from Large Datasets, Spatial Statistics.
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Key Notes -- Classification and Discrimination -- Data Mining -- Robustness and Classification -- Categorical Data and Latent Class Approach -- Latent Variables and Related Methods -- Symbolic, Multivalued and Conceptual Data Analysis -- Spatial, Temporal, Streaming and Functional Data Analysis -- Bio and Health Science.

The growing capabilities in generating and collecting data has risen an urgent need of new techniques and tools in order to analyze, classify and summarize statistical information, as well as to discover and characterize trends, and to automatically bag anomalies. This volume provides the latest advances in data analysis methods for multidimensional data which can present a complex structure: The book offers a selection of papers presented at the first Joint Meeting of the Société Francophone de Classification and the Classification and Data Analysis Group of the Italian Statistical Society. Special attention is paid to new methodological contributions from both the theoretical and the applicative point of views, in the fields of Clustering, Classification, Time Series Analysis, Multidimensional Data Analysis, Knowledge Discovery from Large Datasets, Spatial Statistics.

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