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The Variable Precision Rough Set Inductive Logic Programming Model and Strings |
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| Authors: | V Uma Maheswari Arul Siromoney K M Mehata & K Inoue |
| Affiliation: | School of Computer Science and Engineering, Anna University, Chennai—600 025, India,;School of Computer Science and Engineering, Anna University, Chennai—600 025, India;, Department of Computer Science and Systems Engineering, Faculty of Engineering, Yamaguchi University, Ube 755-8611, Japan |
| Abstract: | The Variable Precision Rough Set Inductive Logic Programming model (VPRSILP model) extends the Variable Precision Rough Set (VPRS) model to Inductive Logic Programming (ILP). The generic Rough Set Inductive Logic Programming (gRS-ILP) model provides a framework for ILP when the setting is imprecise and any induced logic program will not be able to distinguish between certain positive and negative examples. The gRS-ILP model is extended in this paper to the VPRSILP model by including features of the VPRS model. The VPRSILP model is applied to strings and an illustrative experiment on transmembrane domains in amino acid sequences is presented. |
| Keywords: | rough set theory variable precision rough sets inductive logic programming machine learning knowledge discovery from data molecular biology |