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Advances in K-means Clustering: A Data Mining Thinking - Springer Theses Junjie Wu 2012 edition
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Advances in K-means Clustering: A Data Mining Thinking - Springer Theses
Junjie Wu
The K-means algorithm is commonly used in data mining and business intelligence. This award-winning research pioneers its application to the intricacies of 'big data', detailing a theoretical framework for aggregating and validating clusters with K-means.
190 pages, 6 black & white illustrations, 44 colour illustrations, biography
| Mediji | Grāmatas Hardcover Book (Grāmata ar cieto muguriņu un vāku) |
| Izlaists | 2012. gada 10. jūlijs |
| ISBN13 | 9783642298066 |
| Izdevēji | Springer-Verlag Berlin and Heidelberg Gm |
| Lapas | 180 |
| Izmēri | 155 × 235 × 13 mm · 453 g |
| Valoda | Franču |
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