square {lazy.tree}

R Documentation

Test Data for Classification Tree without Error

Description

Test Data for Classification Tree without Error

Usage

square

Format

A data frame with 16 observations and 12 variables

x1

num: the horizontal coordinate (regressor variable)

x1

num: the vertical coordinate (regressor variable)

c1

factor: the horizontal coordinate (regressor variable)

c2

factor: the vertical coordinate (regressor variable)

class1

num: the name of the regions (most simple criterion variable)

class1n

num: the name of the regions (most simple criterion variable)

class2

num: the name of the regions

class3

num: the name of the regions

class4

num: the name of the regions (most complex criterion variable)

class5x

num: the name of the regions (most complex criterion variable)

class5

num: the name of the regions (most complex criterion variable)

#'

class6

num: the name of the regions (6 regions)

Class1

factor: the name of the regions (most simple criterion variable)

Class1n

factor: the name of the regions (most simple criterion variable)

Class2

factor: the name of the regions

Class3

factor: the name of the regions

Class4

factor: the name of the regions (most complex criterion variable)

Class5

factor: the name of the regions (most complex criterion variable)

Class5x

factor: the name of the regions (most complex criterion variable)

Class6

factor: the name of the regions (6 regions)

Details

This data consist of 16 observations of two dimensional data.
A plane was divided into 4 or 5 regeons.

Use below to see the structure:

 plot(square$x1,square$x2, type="n")
 text(square$x1,square$x2,square$Class5, cex=2)
 SQ2=matrix(square$class5, 4,, byrow=1)
 heatmap( t(SQ2), Rowv=NA, Colv=NA, reorderfun=NA, symm=1
        , labRow=4:1, labCol=1:4, revC=TRUE )

 plot(square$x1,square$x2, type="n")
 text(square$x1,square$x2,square$Class6, cex=2)
 SQ2=matrix(square$class6, 4,, byrow=1)
 heatmap( t(SQ2), Rowv=NA, Colv=NA, reorderfun=NA, symm=1
        , labRow=4:1, labCol=1:4, revC=TRUE )
 

Examples of DecTree analysis

res=DecTree( square$Class5, square[,c("x1","x2")], maxdepth=4
             , majestic=0, rf=0
            , print=3, plot=1, title="v", impfuncname="entropy")
ni=node_info_dt( res, depth=400 )

res=DecTree( square$Class5, square[,c("c1","c2")], maxdepth=4, method=4
             , majestic=0, rf=0
             , print=3, plot=1, title="b", impfuncname="entropy")
ni=node_info_dt( res, depth=400 )


 res=DecTree( square$Class6, square[,c("x1","x2")], maxdepth=4
             , majestic=0, rf=0
            , print=3, plot=1, title="b", impfuncname="entropy")
ni=node_info_dt( res, depth=400 )

res=DecTree( square$Class6, square[,c("c1","c2")], maxdepth=4, method=1
             , majestic=0, rf=0
             , print=3, plot=1, title="b", impfuncname="entropy")
ni=node_info_dt( res, depth=400 )

Source

Generated by author.

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