Browsing by Subject "Knowledge Engineering"

Filter results by typing the first few letters
Now showing 1 - 2 of 2
  • Thumbnail Image
    ItemOpen Access
    An overview of regression techniques for knowledge discovery
    (Cambridge University Press, 1999) Uysal, İ.; Güvenir, H. A.
    Predicting or learning numeric features is called regression in the statistical literature, and it is the subject of research in both machine learning and statistics. This paper reviews the important techniques and algorithms for regression developed by both communities. Regression is important for many applications, since lots of real life problems can be modeled as regression problems. The review includes Locally Weighted Regression (LWR), rule-based regression, Projection Pursuit Regression (PPR), instance-based regression, Multivariate Adaptive Regression Splines (MARS) and recursive partitioning regression methods that induce regression trees (CART, RETIS and M5).
  • Thumbnail Image
    ItemOpen Access
    UVT: a unification based tool for knowledge based verification
    (IEEE, 1993) Polat, F.; Guvenir, H. A.
    A method for verifying knowledge bases that is based on the unification of rules is discussed. One characteristic that distinguishes this approach from other verification tools is that it infers some of the rules that are not explicitly given in the rule base and considers their effect on the verification process. The method can determine conflicting, redundant, subsumed, circular, and dead-end rules, redundant if conditions in rules, and cycles and contradictions within rules. The method has been implemented in a computer program called UVT (for unification-based verification tool) and tested on sample knowledge bases.