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 them into areas of interest, such as clustering mixed scale data and incomplete clustering. This work suggests methods for both cluster finding and cluster description, and includes nearly 60 computational exam...
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| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Boca Raton, FL
Chapman & Hall/CRC
2005
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| Series: | Series in computer science and data analysis
volume 3 |
| Subjects: | |
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| 100 | 1 | |a Mirkin, B. G. |q (Boris Grigorʹevich) |e author | |
| 245 | 1 | 0 | |a Clustering for data mining |b a data recovery approach |c Boris Mirkin |
| 264 | 1 | |a Boca Raton, FL |b Chapman & Hall/CRC |c 2005 | |
| 264 | 4 | |c © 2005 | |
| 300 | |a xxiii, 266 pages |b illustrations |c 24 cm. | ||
| 336 | |a text |2 rdacontent | ||
| 337 | |a unmediated |2 rdamedia | ||
| 338 | |a volume |2 rdacarrier | ||
| 490 | 1 | |a Computer science and data analysis series |v volume 3 | |
| 504 | |a Includes bibliographical references and index | ||
| 520 | |a Presents a theory that not only closes gaps in K-Means and Ward methods, but also extends them into areas of interest, such as clustering mixed scale data and incomplete clustering. This work suggests methods for both cluster finding and cluster description, and includes nearly 60 computational examples covering the various stages of clustering | ||
| 592 | |a 60712/005 |b 27/5/2019 |c RM 278.20 |h Amwood | ||
| 650 | 0 | |a Data mining | |
| 650 | 0 | |a Cluster analysis | |
| 830 | 0 | |a Series in computer science and data analysis |v volume 3 | |
| 999 | |a vtls000064155 |c 51149 |d 51149 | ||