A rule-based classifier uses a set of IF-THEN
rules for classification. An IF-THEN rule is an expression of the form IF condition
THEN conclusion. An example is rule
R1: IF age = youth AND student
= yes THEN buys computer = yes
The
“IF”-part (or left-hand side) of a rule is known as the rule antecedent or
precondition. The “THEN”-part (or right-hand side) is the rule consequent. The
rule’s consequent contains a class prediction (in this case, we are predicting
whether a customer will buy a computer)
R1: (age = youth) ^ (student =
yes))(buys computer = yes).
If the condition (that is, all of the
attribute tests) in a rule antecedent holds true for a given tuple,we say that
the rule antecedent is satisfied (or simply, that the rule is satisfied) and
that the rule covers the tuple.
ncovers = no of tuples covered by R
ncorrect = no of tuples correctly classified
by R
coverage(R) = ncovers /|D| /* D: training data set */
accuracy(R) = ncorrect / ncovers
If more than one rule is triggered, need
conflict resolution Tech.
1)Size ordering: assign the highest priority
to the triggering rules that has the “toughest” requirement (i.e., with the
most attribute test)
2)Class-based ordering: decreasing order of
occurrence or misclassification cost per class
3)Rule-based ordering (decision list): rules
are organized into one long priority list, according to some measure of rule
quality or by experts
