It is becoming increasingly apparent that without some form of explanation capability, the full potential of trained Artificial Neural Networks (ANNs) may not be realised. The primary purpose of this report is to survey techniques which have been developed to redress this situation. Specifically the survey focuses on mechanisms, procedures, and algorithms designed to insert knowledge into ANNs ...

In data mining applications, it is important to develop evaluation methods for selecting quality and profitable rules. This paper utilizes a non-parametric approach, Data Envelopment Analysis (DEA), to estimate and rank the efficiency of association rules with multiple criteria. The interestingness of association rules is conventionally measured based on support and confidence. For specific app...

This paper presents a method of using the so-called „bacterial algorithm” [4, 5] for extracting the fuzzy rule base from a training set. The class of membership functions is restricted to trapezoidal, as it is general enough and widely used. The pseudobacterial genetic algorithm (PBGA) is show. The PBGA optimises the trapezoidal membership functions in the rules by the bacterial mutation operat...

In this paper, we present a novel rule evaluation support method for post-processing of mined results with rule evaluation models based on objective indices. Post-processing of mined results is one of the key issues to make a data mining process successfully. However, it is difficult for human experts to evaluate many thousands of rules from a large dataset with noises completely. To reduce the...

Government endorsed security product evaluations completed between 1984 and 1999 show a number of interesting trends. According to official lists maintained by the United States, United Kingdom, and Australia, 242 products were evaluated since the first U.S. evaluations in 1984. The evaluations show trends in the number of evaluations performed, which evaluations are performed and where, what e...

Classification aims to map a data instance to its appropriate class (or label). In associative classification the mapping is done through an association rule with the consequent restricted to the class attribute. Eager associative classification algorithms build a single rule set during the training phase, and this rule set is used to classify all test instances. Lazy algorithms, however, do no...

introduction: today, medical software are used in different aspects of healthcare varying from simple data processing to collection and interpretation of physiological information and education of nurses and physicians. to ensure use of medical software, they must be constantly evaluated based on specific criteria. since there is no organized evaluation system and comprehensive criteria for eva...

This paper describes the main features of a knowledge-based system evaluation method. System evaluation is placed in the context of a hybrid legal decision-support system, Advisory Support for Home Settlement in Divorce (ASHSD). Legal knowledge for ASHSD is represented in two forms, as rules and previously decided cases. Besides distinguishing the two different forms of knowledge representation...

The importance of inference rules to semantic applications has long been recognized and extensive work has been carried out to automatically acquire inference-rule resources. However, evaluating such resources has turned out to be a non-trivial task, slowing progress in the field. In this paper, we suggest a framework for evaluating inference-rule resources. Our framework simplifies a previousl...