R: Wrapper function of missing value completion

MV.missingValueCompletion {RoughSets} | R Documentation

## Wrapper function of missing value completion

### Description

It is a wrapper function for missing value completion.

### Usage

    MV.missingValueCompletion(decision.table, type.method = "deletionCases")

### Arguments

`decision.table` | a `"DecisionTable"` class representing a decision table. See `SF.asDecisionTable`. Note: missing values are recognized as NA.
`type.method` | one of the following methods: `"deletionCases"`: See `MV.deletionCases`. `"mostCommonValResConcept"`: See `MV.mostCommonValResConcept`. `"mostCommonVal"`: See `MV.mostCommonVal`. `"globalClosestFit"`: See `MV.globalClosestFit`. `"conceptClosestFit"`: See `MV.conceptClosestFit`.

### Value

A class `"MissingValue"` which contains

- `val.NA`: a matrix containing indices of missing value (i.e., unknown values) positions and their values.

- `type.method`: a string showing the type of used method. In this case, it is `"deleteCases"`.

### Author(s)

Lala Septem Riza

### References

J. Grzymala-Busse and W. Grzymala-Busse, "Handling Missing Attribute Values," in Data Mining and Knowledge Discovery Handbook, O. Maimon and L. Rokach, Eds. New York : Springer, 2010, pp. 33-51

### See Also

`MV.deletionCases`, `MV.mostCommonValResConcept`, `MV.mostCommonVal`, `MV.globalClosestFit`, and `MV.conceptClosestFit`.

### Examples

    #############################################
    ## Example :
    #############################################
    dt.ex1 <- data.frame(
         c(100.2, 102.6, NA, 99.6, 99.8, 96.4, 96.6, NA),
         c(NA, "yes", "no", "yes", NA, "yes", "no", "yes"),
         c("no", "yes", "no", "yes", "yes", "no", "yes", NA),
         c("yes", "yes", "no", "yes", "no", "no", "no", "yes"))
    colnames(dt.ex1) <- c("Temp", "Headache", "Nausea", "Flu")
    decision.table <- SF.asDecisionTable(dataset = dt.ex1, decision.attr = 4,
                                        indx.nominal = c(2:4))
    indx = MV.missingValueCompletion(decision.table, type.method = "deletionCases")

    ## generate new decision table
    new.decTable <- SF.applyDecTable(decision.table, indx)

[Package RoughSets version 1.3-7 Index]