MV.mostCommonVal function

Replacing missing attribute values by the attribute mean or common values

It is used for handling missing values by replacing the attribute mean or common values. If an attributes containing missing values is continuous/real, the method uses mean of the attribute instead of the most common value. In order to generate a new decision table, we need to execute SF.applyDecTable.

MV.mostCommonVal(decision.table)

Arguments

• decision.table: a "DecisionTable" class representing a decision table. See SF.asDecisionTable. Note: missing values are recognized as NA.

Returns

A class "MissingValue". See MV.missingValueCompletion.

Examples

#############################################
## Example: Replacing missing attribute values
##          by the attribute mean/common values
#############################################
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.mostCommonVal(decision.table)

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.missingValueCompletion

Author(s)

Lala Septem Riza