KAPSAMA YAKLAŞIMINA GÖRE KURAL ÜRETEN BİLGİ KEŞFİ ALGORİTMALARINDA ENTROPİ KULLANIMI

The objective of this paper is to introduce the use of entropy for knowledge acquisition in the algorithms which use the covering approach in inductive learning. REX-1 and REX-2 algorithms, which generate rules based on the covering approach, are compared with other algorithms using the same principle. These algorithms which adapt the mentioned approach generate rules using the search methods. As is used in the algorithms generating the decision tree, the entropy can be used as well in algorithms which utilize the covering approach. While generating rules by search methods, it is vital that the algorithms give priority to the attributes with high complexity in an example set. However, use of entropy attaches the priority to the attributes with lower complexity. ID3 and C4.5 algorithms may be cited among those using the entropy. Instead of direct rule generation, but they use the decision tree to induce rules.