Showing 1 - 7 of 7
A key problem in the development of information systems is understanding features of the development process. To this end, in recent years, considerable interest has been focused on modelling processes. In this paper, the results of an empirical investigation into the use of prototyping in...
Persistent link: https://www.econbiz.de/10009477575
The upstream activities of software development are often viewed as both the most important, in terms of cost, and the yet the least understood, and most problematic, particularly in terms of satisfying customer requirements. Business process modelling is one solution that is being increasingly...
Persistent link: https://www.econbiz.de/10009429740
The use of formal models such as Role Activity Diagrams (RADs) for analysing a process often hide what really happens during that process. In this paper, we build on previous research on informal aspects of the prototyping process and look at the key concerns that prototypers had during the...
Persistent link: https://www.econbiz.de/10009429748
In this paper a classification framework for incomplete data, based on electrostatic field model is proposed. An original approach to exploiting incomplete training data with missing features, involving extensive use of electrostatic charge analogy, has been used. The framework supports a hybrid...
Persistent link: https://www.econbiz.de/10009429779
Estimation of the generalization ability of a predictive model is an important issue, as it indicates expected performance on previously unseen data and is also used for model selection. Currently used generalization error estimation procedures like cross–validation (CV) or bootstrap are...
Persistent link: https://www.econbiz.de/10009429791
Estimation of the generalization ability of a predictive model is an important issue, as it indicates expected performance on previously unseen data and is also used for model selection. Currently used generalization error estimation procedures like cross–validation (CV) or bootstrap are...
Persistent link: https://www.econbiz.de/10009429864
In this paper a classification framework for incomplete data, based on electrostatic field model is proposed. An original approach to exploiting incomplete training data with missing features, involving extensive use of electrostatic charge analogy, has been used. The framework supports a hybrid...
Persistent link: https://www.econbiz.de/10009429890