Аннотация
Data mining in the form of rule discovery is a growing
field of investigation. A recent addition to this field
is the use of evolutionary algorithms in the mining
process. While this has been used extensively in the
traditional mining of relational databases, it has
hardly, if at all, been used in mining sequences and
time series. In this paper we describe our method for
evolutionary sequence mining, using a specialized piece
of hardware for rule evaluation, and show how the
method can be applied to several different mining
tasks, such as supervised sequence prediction,
unsupervised mining of interesting rules, discovering
connections between separate time series, and
investigating tradeoffs between contradictory
objectives by using multiobjective evolution.
Пользователи данного ресурса
Пожалуйста,
войдите в систему, чтобы принять участие в дискуссии (добавить собственные рецензию, или комментарий)