Titlebook: Research and Development in Intelligent Systems XVI; Proceedings of ES99, Max Bramer,Ann Macintosh,Frans Coenen Conference proceedings 2000

reaching

Learning Lazy Rules to Improve the Performance of Classifiers rule only when classifying a test case. The objective of the framework is to improve the performance of a base learning algorithm. It has the potential to be used for different types of base learning algorithms. L.R. performs attribute elimination and training case selection using cross-validation

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resistant

Generosity

Automating Case Selection in the Construction of a Case Libraryd by evaluation of the additional coverage provided by candidate cases. Cases that can be solved by the addition of a candidate case to the library are discovered in the approach by reversing the direction of case-based reasoning. The computational effort required in the evaluation of candidate case

难理解

Improving a Distributed Case-Based Reasoning System Using Introspective Learningn that supports engineering sales staff. The application operates on the world wide web and uses the XML standard as a communications protocol between client and server side Java applets. The paper briefly describes the distributed architecture of the application, the two case retrieval techniques u

Mucosa

Structured Cases in CBR — Re-using and Adapting Cases for Time-tabling Problemse timetables from previously solved problems are employed to aid in the generation of solutions for new time-tabling problems. A list of feature-value pairs is insufficient to represent all the necessary information. We show that attribute graphs can be used to represent information such as the rela

发牢骚

Roget’s Thesaurus: An additional knowledge source for Textual CBR?uct cases in a case base that is indexed using a manually identified vocabulary. A domain dependant similarity function is then required to recognise appropriate cases for a user’s query. This paper describes a new similarity measure for Textual CBR that can be applied to any text. The measure is ba

出汗

取消

The KRAFT Architecture for Knowledge Fusion and Transformationtocol. Facilitator agents perform matchmaking and brokerage services between the various kinds of agent. KRAFT is being applied to an example application in the domain of network data services design.

流出

Learning Lazy Rules to Improve the Performance of Classifiersier for each test case than the classifier trained using all attributes and all training cases. We show empirically that L.R. improves the performances of naive Bayesian classifiers and majority vote.