Data Mining: Practical Machine Learning Tools and Techniques, Second Edition

to radically different results. A different problem occurs when an instance is

encountered that the rules fail to classify at all. Again, this cannot occur with

decision trees, or with rules read directly off them, but it can easily happen with

general rule sets. One way of dealing with this situation is to fail to classify such

an example; another is to choose the most frequently occurring class as a default.

Again, radically different results may be obtained for these strategies. Individ-

ual rules are simple, and sets of rules seem deceptively simple—but given just

a set of rules with no additional information, it is not clear how it should be

interpreted.

A particularly straightforward situation occurs when rules lead to a class that

is Boolean (say,yesand no) and when only rules leading to one outcome (say,

yes) are expressed. The assumption is that if a particular instance is not in class

68 CHAPTER 3| OUTPUT: KNOWLEDGE REPRESENTATION

x

y

1 2 3

a

1

z

2

3

w

1

b

2

b

3

a

1

b

2

b

3

If x=1 and y=1 then class = a

If z=1 and w=1 then class = a

Otherwise class = b

Figure 3.4Decision tree with a replicated subtree.