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In-Depth Information
of attributes in
S
. The time complexity of the action tree algorithm is (
k
∗
n
)+(2
k
1) =
O
(
n
), where
n
is the number of classification rules,
k
is
the number of attributes in
S
. The action tree algorithm is simpler and more
e
cient then the action forest algorithm.
∗
n
∗
5 Conclusion
Discovering a set of rules is not the end of knowledge discovery process. A rule
is interesting, if it meets some user specified thresholds. As knowledge discov-
ery techniques are increasingly used to solve real life problems, a significant
need exists for a new generation of technique, e-action rules mining, with the
ability to facilitate human beings in evaluating and interpreting the discov-
ered patterns. Additionally, as the value of data is related to how quickly and
effectively the data can be reduced, explored, manipulated and managed, we
propose a new strategy, action-tree algorithm for discovering e-action rules.
Our results show that actionability can be considered as a partially objective
measure rather than a purely subjective one.
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