Evaluation of methods/software is considered as a very important procedure for any user who wants to know the actual performance of a scientific tool. For the implementation of such evaluation procedure several test cases - scenarios shall be run. Obtaining the necessary test data sets can be an obstacle due to both privacy issues and also the time and cost associated with collecting multiple instances of a diverse set of data sources. An efficient alternative is the design and use of synthetic reference data sets to undertake black-box testing. These data sets should be generated in a manner consistent with the functional specification of the problem addressed by the method/software. According to this approach a data set generator was developed for the evaluation of preference disaggregation methods that are used for customer satisfaction analysis, like MUSA (Multicriteria Satisfaction Analysis).
Features
- Data sets
- Generator
- Algorithm
- Satisfaction Survey
Project Samples
