Package smile.association
Class ARM
java.lang.Object
smile.association.ARM
 All Implemented Interfaces:
Iterable<AssociationRule>
Association Rule Mining.
Let
I = {i_{1}, i_{2},..., i_{n}}
be a set of n binary attributes called items. Let
D = {t_{1}, t_{2},..., t_{m}}
be a set of transactions called the database. Each transaction in
D
has a unique transaction ID and contains a subset of
the items in I
. An association rule is defined as an
implication of the form X ⇒ Y
where X, Y ⊆ I
and X ∩ Y = Ø
.
The item sets X
and Y
are called antecedent
(lefthandside or LHS)
and consequent (righthandside or RHS) of the rule, respectively.
The support supp(X)
of an item set X is defined as
the proportion of transactions in the database which contain the item set.
Note that the support of an association rule X ⇒ Y
is
supp(X ∪ Y)
. The confidence of a rule is defined
conf(X ⇒ Y) = supp(X ∪ Y) / supp(X)
.
Confidence can be interpreted as an estimate of the probability
P(Y  X)
, the probability of finding the RHS of the
rule in transactions under the condition that these transactions
also contain the LHS. Association rules are usually required to
satisfy a userspecified minimum support and a userspecified
minimum confidence at the same time.
Method Summary
Modifier and TypeMethodDescriptionstatic Stream
<AssociationRule> Mines the association rules.iterator()
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
Methods inherited from interface java.lang.Iterable
forEach, spliterator

Method Details

iterator
 Specified by:
iterator
in interfaceIterable<AssociationRule>

apply
Mines the association rules. Parameters:
confidence
 the confidence threshold for association rules.tree
 the FPtree. Returns:
 the stream of association rules.
