Sequential Update of ADtrees (2006)

Josep Roure, Andrew W. Moore

Tags

AD-Trees, Incremental Learning

Abstract

Ingcreasingly, data-mining algorithms must
deal with databases that continuously grow
over time. These algorithms must avoid re-
peatedly scanning their databases. When
database attributes are symbolic, ADtrees
have already shown to be efficient structures
to store sufficient statistics in main memory
and to accelerate the mining process in batch
environments. Here we present an efficient
method to sequentially update ADtrees that
is suitable for incremental environments.

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Approximate BibTeX Entry

@inproceedings{incremADtrees06,
    Year = {2006},
    Pages = {769-776},
    Publisher = {ACM},
    Booktitle = {ICML},
    Editor = {William W. Cohen and Andrew Moore},
    Author = { Josep Roure, Andrew W. Moore },
    Title = {Sequential Update of ADtrees}
}