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Hierarchical Time-Series Clustering for Data
Streams
by Pedro Rodrigues et al.
KDD’04
Piyush Ranjan Satapathy
A class Presentation for
CS235: Data Mining Techniques
ODAC Algorithm
1. Get nmin next examples
2. Update and propagate sufficient statistics for all variables
3. Compute the Hoeffding bound
4. Choose next cluster Ck in descending order of diameters
5. TestSplit() in cluster Ck
6. If we found a split point, goto 12. with new cluster tree
7. If still exists a cluster Ck not yet tested for splitting goto 4.
8. Choose next cluster Ck in ascending order of diameters
9. TestAggregate() in cluster Ck
10. If we found an aggregation then goto 12. with new cluster tree
11. If still exists a cluster Ck not yet tested for aggregation goto 8.
12. If not end of data, goto 1.
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