discernibilityMatrix: DISCERNIBILITY MATRIX
In albhasan/RoughSetKnowledgeReduction: Simplification of Decision Tables using Rough Sets
Description
Usage
Arguments
Value
Author(s)
References
See Also
Examples
Description
Objects of this class are not meant to be directly created by users; instead, they are created by the objects of the class Discernibility Matrix.
Usage
1
discernibilityMatrix(theDiscernibilityMatrix)
Arguments
theDiscernibilityMatrix
A boolean 3 dimension array
Value
It returns a Discernibility Matrix object.
Author(s)
Alber Sanchez alber.sanchez@uni-muenster.de
References
Pawlak, Zdzislaw 1991 Rough Sets: Theoretical Aspects of Reasoning About Data Dordrecht: Kluwer Academic Publishing.
See Also
Examples
1
2
3
4
exampleMatrix2 <- matrix(c(1,1,0,1,1,2,2,0,0,0,1,1,1,2,0,0,0,
0,0,0,2,1,0,0,1,2,2,2,1,1,0,0,2,2,2),ncol = 5)
dt <- new(Class="DecisionTable",decisionTable = exampleMatrix2)
dm <- computeDiscernibilityMatrix(dt)
albhasan/RoughSetKnowledgeReduction documentation built on May 11, 2019, 10:29 p.m.
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Description Usage Arguments Value Author(s) References See Also Examples
Description
Objects of this class are not meant to be directly created by users; instead, they are created by the objects of the class Discernibility Matrix.
Usage
1 | discernibilityMatrix(theDiscernibilityMatrix)
|
Arguments
theDiscernibilityMatrix |
A boolean 3 dimension array |
Value
It returns a Discernibility Matrix object.
Author(s)
Alber Sanchez alber.sanchez@uni-muenster.de
References
Pawlak, Zdzislaw 1991 Rough Sets: Theoretical Aspects of Reasoning About Data Dordrecht: Kluwer Academic Publishing.
See Also
Examples
1 2 3 4 | exampleMatrix2 <- matrix(c(1,1,0,1,1,2,2,0,0,0,1,1,1,2,0,0,0,
0,0,0,2,1,0,0,1,2,2,2,1,1,0,0,2,2,2),ncol = 5)
dt <- new(Class="DecisionTable",decisionTable = exampleMatrix2)
dm <- computeDiscernibilityMatrix(dt)
|
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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