Screen LibraryModel-based clustering, classification, and density estimation using mclust in R /
"Model-based clustering and classification methods provide a systematic statistical approach to clustering, classification, and density estimation via mixture modeling. The model-based framework allows the problems of choosing or developing methods to be understood within the context of statist...
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| Main Authors: | |
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| Group Author: | ; ; |
| Published: |
CRC Press,
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| Publisher Address: | Boca Raton, FL : |
| Publication Dates: | 2023. |
| Literature type: | Book |
| Language: | English |
| Edition: | First edition. |
| Series: |
Chapman & Hall/CRC the R series
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| Subjects: | |
| Summary: |
"Model-based clustering and classification methods provide a systematic statistical approach to clustering, classification, and density estimation via mixture modeling. The model-based framework allows the problems of choosing or developing methods to be understood within the context of statistical modeling"-- |
| Carrier Form: | xxvi, 242 pages : illustrations (chiefly color) ; 24 cm. |
| Bibliography: | Includes bibliographical references (pages 227-239) and index. |
| ISBN: |
9781032234953 1032234954 9781032234960 1032234962 |
| Index Number: | QA278 |
| CLC: |
TP312.8R O212.4-37 |
| Call Number: | O212.4-37/S435 |
| Contents: | Finite mixture models -- Model-based clustering -- Mixture-based classification -- Model-based density estimation -- Visualizing Gaussian mixture models -- Miscellanea. |