2.3 Unknown Information

The problem of unknown information is twofold. It raises problems during the learning phase and also in classification. The latter point is discussed in section 3.

YAILS system deals with two types of unknown information. The first arises when the value of some attribute is "unknown" and the second when the value is irrelevant. While the first case is interpreted as a kind of noise (thus presenting a problem) the second one is treated as a "don't care" situation (the human expert which has provided the examples to the system, may state that the attribute is irrelevant).

Before modifying the current theory to incorporate a new example, YAILS verifies whether the example is already covered. Both kinds of unknowns referred above may present some difficulties. These arise if one (or more) conditions of a rule tests an attribute for which the example has an "unknown" value. YAILS adopts a probabilistic strategy when dealing with this situation. A conditional probability is calculated as follows :.

(2)

where Aj = Vj ... Ak = Vk are the conditions satisfied by the example
and Ai = Vi is the condition of the rule for which the example has an "unknown"
value.

Example :

This probability estimate is used to decide whether the example satisfies the rule. The decision requires a threshold that is user-definable.

The case when there is no information about some attribute is in fact stating that any rule with a condition with that attribute is not satisfied by the example.