Abstract
Non-Deterministic Outlier Detection Method Based on the Variable Precision Rough Set Model
Highlights
Non-determ i n istic outl ier detection method based on the variable precision rough set model
RelyinS on the nondcterministic characterprovided by the Va¡iable Precision Rough Set Model (VPRSM) and by the relaxatio¡ ofthe§et inclus¡on concepa thüt allows the úa¡aSemcnt ofcenair thrqsholds set t y the use., we propose a new modcl in this study based on the VPRSM a¡d cre¡te a neu algorithm based on thc algo
The method is computationally feasible for large datas€§, ar¡d to demonsuat this, we proposed an Rough Set Basic Model (RSBM)-based ourlierdetection algorilhm with a oo0-expole¡tial teúporal and spatial comptexily ordcr
Summary
Non-determ i n istic outl ier detection method based on the variable precision rough set model. This p(xcsscould ¡lport lnowlcdte findings of str¡tcgic imponance in a widc tange of a¡plicatioos: fraud detect¡on, the dctcction Resurcher create m(xlels, algorithms and functi
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
