Controlled redundancy in incremental rule learning
L Torgo - European Conference on Machine Learning, 1993 - Springer
European Conference on Machine Learning, 1993•Springer
This paper introduces a new concept learning system. Its main features are presented and
discussed. The controlled use of redundancy is one of the main characteristics of the
program. Redundancy, in this system, is used to deal with several types of uncertainty
existing in real domains. The problem of the use of redundancy is addressed, namely its
influence on accuracy and comprehensibility. Extensive experiments were carried out on
three real world domains. These experiments showed clearly the advantages of the use of …
discussed. The controlled use of redundancy is one of the main characteristics of the
program. Redundancy, in this system, is used to deal with several types of uncertainty
existing in real domains. The problem of the use of redundancy is addressed, namely its
influence on accuracy and comprehensibility. Extensive experiments were carried out on
three real world domains. These experiments showed clearly the advantages of the use of …
Abstract
This paper introduces a new concept learning system. Its main features are presented and discussed. The controlled use of redundancy is one of the main characteristics of the program. Redundancy, in this system, is used to deal with several types of uncertainty existing in real domains. The problem of the use of redundancy is addressed, namely its influence on accuracy and comprehensibility. Extensive experiments were carried out on three real world domains. These experiments showed clearly the advantages of the use of redundancy.
Springer
以上显示的是最相近的搜索结果。 查看全部搜索结果