Matches in SemOpenAlex for { <https://semopenalex.org/work/W2020170857> ?p ?o ?g. }
- W2020170857 abstract "Z. Pawlak’s rough set theory has been widely applied in analyzing ordinary information systems and decision tables. While few studies have been conducted on attribute selection problem in incomplete decision systems because of its complexity. Therefore, it is necessary to investigate effective algorithms to tackle this issue. In this paper, In this paper, a new rough conditional entropy based uncertainty measure is introduced to evaluate the significance of subsets of attributes in incomplete decision systems. Moreover, some important properties of rough conditional entropy are derived and three attribute selection approaches are constructed, including an exhaustive approach, a heuristic approach, and a probabilistic approach. In the end, a series of experiments on practical incomplete data sets are carried out to assess the proposed approaches. The final experimental results indicate that two of these approaches perform satisfyingly in the process of attribute selection in incomplete decision systems." @default.
- W2020170857 created "2016-06-24" @default.
- W2020170857 creator A5048916368 @default.
- W2020170857 creator A5072523484 @default.
- W2020170857 date "2014-09-01" @default.
- W2020170857 modified "2023-09-27" @default.
- W2020170857 title "A Novel Approach Based on Rough Conditional Entropy for Attribute Reduction" @default.
- W2020170857 cites W1488636611 @default.
- W2020170857 cites W1565313879 @default.
- W2020170857 cites W1574650370 @default.
- W2020170857 cites W1967116708 @default.
- W2020170857 cites W1967689665 @default.
- W2020170857 cites W1969045113 @default.
- W2020170857 cites W1976622705 @default.
- W2020170857 cites W1978777492 @default.
- W2020170857 cites W1985606733 @default.
- W2020170857 cites W1994743372 @default.
- W2020170857 cites W1995902269 @default.
- W2020170857 cites W1999400580 @default.
- W2020170857 cites W2004030345 @default.
- W2020170857 cites W2004068299 @default.
- W2020170857 cites W2018406196 @default.
- W2020170857 cites W2026972946 @default.
- W2020170857 cites W2035742098 @default.
- W2020170857 cites W2064255812 @default.
- W2020170857 cites W2070073440 @default.
- W2020170857 cites W2071922386 @default.
- W2020170857 cites W2095290023 @default.
- W2020170857 cites W2103514965 @default.
- W2020170857 cites W2104196441 @default.
- W2020170857 cites W2108653163 @default.
- W2020170857 cites W2110130189 @default.
- W2020170857 cites W2122567334 @default.
- W2020170857 cites W2126072717 @default.
- W2020170857 cites W2140349414 @default.
- W2020170857 cites W2143040521 @default.
- W2020170857 cites W2147828565 @default.
- W2020170857 cites W2158481371 @default.
- W2020170857 cites W2171053395 @default.
- W2020170857 cites W2171759229 @default.
- W2020170857 cites W2913196191 @default.
- W2020170857 cites W2990482619 @default.
- W2020170857 cites W3149389529 @default.
- W2020170857 cites W4250395409 @default.
- W2020170857 cites W4255833381 @default.
- W2020170857 doi "https://doi.org/10.4028/www.scientific.net/amm.644-650.1607" @default.
- W2020170857 hasPublicationYear "2014" @default.
- W2020170857 type Work @default.
- W2020170857 sameAs 2020170857 @default.
- W2020170857 citedByCount "2" @default.
- W2020170857 countsByYear W20201708572015 @default.
- W2020170857 countsByYear W20201708572018 @default.
- W2020170857 crossrefType "journal-article" @default.
- W2020170857 hasAuthorship W2020170857A5048916368 @default.
- W2020170857 hasAuthorship W2020170857A5072523484 @default.
- W2020170857 hasConcept C101721835 @default.
- W2020170857 hasConcept C106301342 @default.
- W2020170857 hasConcept C106752470 @default.
- W2020170857 hasConcept C111012933 @default.
- W2020170857 hasConcept C119857082 @default.
- W2020170857 hasConcept C121332964 @default.
- W2020170857 hasConcept C124101348 @default.
- W2020170857 hasConcept C154945302 @default.
- W2020170857 hasConcept C33923547 @default.
- W2020170857 hasConcept C39105242 @default.
- W2020170857 hasConcept C41008148 @default.
- W2020170857 hasConcept C49937458 @default.
- W2020170857 hasConcept C62520636 @default.
- W2020170857 hasConcept C75814411 @default.
- W2020170857 hasConcept C84839998 @default.
- W2020170857 hasConcept C9679016 @default.
- W2020170857 hasConceptScore W2020170857C101721835 @default.
- W2020170857 hasConceptScore W2020170857C106301342 @default.
- W2020170857 hasConceptScore W2020170857C106752470 @default.
- W2020170857 hasConceptScore W2020170857C111012933 @default.
- W2020170857 hasConceptScore W2020170857C119857082 @default.
- W2020170857 hasConceptScore W2020170857C121332964 @default.
- W2020170857 hasConceptScore W2020170857C124101348 @default.
- W2020170857 hasConceptScore W2020170857C154945302 @default.
- W2020170857 hasConceptScore W2020170857C33923547 @default.
- W2020170857 hasConceptScore W2020170857C39105242 @default.
- W2020170857 hasConceptScore W2020170857C41008148 @default.
- W2020170857 hasConceptScore W2020170857C49937458 @default.
- W2020170857 hasConceptScore W2020170857C62520636 @default.
- W2020170857 hasConceptScore W2020170857C75814411 @default.
- W2020170857 hasConceptScore W2020170857C84839998 @default.
- W2020170857 hasConceptScore W2020170857C9679016 @default.
- W2020170857 hasLocation W20201708571 @default.
- W2020170857 hasOpenAccess W2020170857 @default.
- W2020170857 hasPrimaryLocation W20201708571 @default.
- W2020170857 hasRelatedWork W1531461924 @default.
- W2020170857 hasRelatedWork W1973866957 @default.
- W2020170857 hasRelatedWork W1974162715 @default.
- W2020170857 hasRelatedWork W1982250082 @default.
- W2020170857 hasRelatedWork W1991826700 @default.
- W2020170857 hasRelatedWork W2037024427 @default.
- W2020170857 hasRelatedWork W2060187158 @default.
- W2020170857 hasRelatedWork W2077534041 @default.
- W2020170857 hasRelatedWork W2128333968 @default.
- W2020170857 hasRelatedWork W2134533842 @default.