A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf
.
Hybridization of Rough Sets and Statistical Learning Theory
[chapter]
2011
Lecture Notes in Computer Science
In this paper we propose the hybridization of the rough set concepts and statistical learning theory. We introduce new estimators for rule accuracy and coverage, which base on the assumptions of the statistical learning theory. These estimators allow us to select rules describing statistically significant dependencies in data. Then we construct classifier which uses these estimators for rule induction. In order to make our solution applicable for information systems with missing values and
doi:10.1007/978-3-642-18302-7_3
fatcat:esxfsj26frgzpft3fng2qzpqfq