Clustering for data mining : a data recovery approach / Boris Mirkin.
"Rather than the traditional set of ad hoc techniques, Clustering for Data Mining: A Data Recovery Approach presents a theory that not only closes gaps in K-Means and Ward methods, but also extends the methods into areas of current interest, such as clustering mixed scale data and incomplete cl...
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| Main Author: | |
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| Format: | Book |
| Language: | English |
| Published: |
Boca Raton, FL :
Chapman & Hall/CRC,
2005.
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| Series: | Computer science and data analysis series ;
3. |
| Subjects: |
| Summary: | "Rather than the traditional set of ad hoc techniques, Clustering for Data Mining: A Data Recovery Approach presents a theory that not only closes gaps in K-Means and Ward methods, but also extends the methods into areas of current interest, such as clustering mixed scale data and incomplete clustering. The author suggests original methods for both cluster finding and cluster description; addresses related topics such as principal component analysis, contingency measures, and data visualization; and includes nearly 60 computational examples covering all stages of clustering, from data preprocessing to cluster validation and results interpretation."--BOOK JACKET. |
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| Physical Description: | xxiii, 266 pages : illustrations ; 24 cm. |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 1584885343 9781584885344 |