Titlebook: Machine Learning: ECML-95; 8th European Confere Nada Lavrac,Stefan Wrobel Conference proceedings 1995 Springer-Verlag Berlin Heidelberg 199

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书目名称Machine Learning: ECML-95影响因子(影响力)




书目名称Machine Learning: ECML-95影响因子(影响力)学科排名




书目名称Machine Learning: ECML-95网络公开度




书目名称Machine Learning: ECML-95网络公开度学科排名




书目名称Machine Learning: ECML-95被引频次




书目名称Machine Learning: ECML-95被引频次学科排名




书目名称Machine Learning: ECML-95年度引用




书目名称Machine Learning: ECML-95年度引用学科排名




书目名称Machine Learning: ECML-95读者反馈




书目名称Machine Learning: ECML-95读者反馈学科排名

吹牛者

Multiple-Knowledge Representations in concept learning,owledge level to build an . correct . description of it. This approach is illustrated through our GEM system which learns concepts in a numerical attribute space using a Neural Network representation as the deep knowledge level and symbolic rules as the shallow level.

ear-canal

Enliven

NADIR

Learning abstract planning cases,troduced model. An empirical study in the domain of process planning in mechanical engineering shows significant improvements in planning efficiency through learning abstract cases while an explanation-based learning method only causes a very slight improvement.

讨好美人

演绎

讨好美人

心胸狭窄

euphoria

Analogical logic program synthesis from examples,d, two programs are said to be similar if they share a common explanation structure at an abstract level. Using this notion of similarity, we formalize an analogical logic program synthesis and show that our algorithm based on a framework of model inference can identify a desired program.