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Learning uncertain rules with CONDORCKD (2007)
| Content Provider | CiteSeerX |
|---|---|
| Author | Fisseler, Jens Kern-Isberner, Gabriele Beierle, Christoph |
| Description | CONDORCKD is a system implementing a novel approach to discovering knowledge from data. It addresses the issue of relevance of the learned rules by algebraic means and explicitly supports the subsequent processing by probabilistic reasoning. After briefly summarizing the key ideas underlying CONDORCKD, the purpose of this paper is to present a walk-through and system demonstration. |
| File Format | |
| Language | English |
| Publisher | AAAI Press |
| Publisher Date | 2007-01-01 |
| Publisher Institution | Proceedings of the Twentieth International Florida Artificial Intelligence Research Society Conference, 74–79 |
| Access Restriction | Open |
| Subject Keyword | Subsequent Processing Novel Approach Key Idea Uncertain Rule System Demonstration Algebraic Mean Probabilistic Reasoning |
| Content Type | Text |
| Resource Type | Article |
