基本信息

· 书名:Multistrategy Learning

· 作者:Michalski

· ISBN13:9780792393740

· 装帧:精装

· 语种:英文

· 出版日期:1993-06-30

· 出版社:Springer US

· 页数:155

· 重量:0.4 kg

· 尺寸:24.4 x 16.6 x 1.6 cm

* 页面参数仅供参考，具体以实物为准.

------ 书籍简介 ------

Most machine learning research has been concerned with the development of systems that implememnt one type of inference within a single representational paradigm Such systems which can be called monostrategy learning systems include those for empirical induction of decision trees or rules explanation based generalization neural net learning from examples genetic algorithm based learning and others Monostrategy learning systems can be very effective and useful if learning problems to which they are applied are sufficiently narrowly defined
Many real world applications however pose learning problems that go beyond the capability of monostrategy learning methods In view of this recent years have witnessed a growing interest in developing multistrategy systems which integrate two or more inference types and or paradigms within one learning system Such multistrategy systems take advantage of the complementarity of different inference types or representational mechanisms Therefore they have a potential to be more versatile and more powerful than monostrategy systems On the other hand due to their greater complexity their development is significantly more difficult and represents a new great challenge to the machine learning community
Multistrategy Learning contains contributions characteristic of the current research in this area