RoughSets (version 1.0-0)

summary.RuleSetFRST: The summary function of rules based on FRST

Description

This function enables the output of a summary of the rule induction methods.

Usage

## S3 method for class 'RuleSetFRST':
summary(object, ...)

Arguments

object

a "RuleSetFRST" object. See RI.hybridFS.FRST and RI.GFRS.FRST.

...

the other parameters.

Value

• a description that contains the following information. For FRST model:
  • The type of the considered model.
  • The type of the considered method.
  • The type of the considered task.
  • The type of similarity.
  • The type of triangular norm.
  • The names of attributes and their type (whether nominal or not).
  • The interval of the data.
  • the variance values of the data.
  • The rules. Every rule constitutes two parts which are IF and THEN parts. For example,"IF pres is around 90 and preg is around 8 THEN class is 2". SeeRI.GFRS.FRST.

Examples

###########################################################
## Example 1: Regression problem
###########################################################
data(RoughSetData)
decision.table <- RoughSetData$housing7.dt

control <- list(type.aggregation = c("t.tnorm", "lukasiewicz"), type.relation =
                c("tolerance", "eq.3"), t.implicator = "lukasiewicz")
res.1 <- RI.hybridFS.FRST(decision.table, control)

summary(res.1)
###########################################################
## Example 2: Classification problem
##############################################################
data(RoughSetData)
decision.table <- RoughSetData$pima7.dt

control <- list(type.aggregation = c("t.tnorm", "lukasiewicz"), type.relation =
                c("tolerance", "eq.3"), t.implicator = "lukasiewicz")
res.2 <- RI.hybridFS.FRST(decision.table, control)

summary(res.2)