symbolicDA (version 0.7-1)

draw.decisionTree.SDA: Draws optimal split based decision tree for symbolic objects

Description

Draws optimal split based decision tree for symbolic objects

Usage

draw.decisionTree.SDA(decisionTree.SDA,boxWidth=1,boxHeight=3)

Value

A draw of optimal split based decision (classification) tree for symbolic objects.

Arguments

decisionTree.SDA

optimal split based decision tree for symbolic objects (result of decisionTree.SDA function)

boxWidth

witdh of single box in drawing

boxHeight

height of single box in drawing

Author

Andrzej Dudek Marcin Pełka

Department of Econometrics and Computer Science, University of Economics, Wroclaw, Poland http://keii.ue.wroc.pl/symbolicDA/

Details

Draws optimal split based decision (classification) tree for symbolic objects.

References

Billard L., Diday E. (eds.) (2006), Symbolic Data Analysis, Conceptual Statistics and Data Mining, John Wiley & Sons, Chichester.

Bock H.H., Diday E. (eds.) (2000), Analysis of symbolic data. Explanatory methods for extracting statistical information from complex data, Springer-Verlag, Berlin.

Diday E., Noirhomme-Fraiture M. (eds.) (2008), Symbolic Data Analysis with SODAS Software, John Wiley & Sons, Chichester.

See Also

decisionTree.SDA

Examples

# LONG RUNNING - UNCOMMENT TO RUN
# Files samochody.xml and wave.xml needed in this example 
# can be found in /inst/xml library of package

# Example 1
#sda<-parse.SO("samochody")
#tree<-decisionTree.SDA(sda, "Typ_samochodu~.", testSet=26:33)
#draw.decisionTree.SDA(tree,boxWidth=1,boxHeight=3)

# Example 2
#sda<-parse.SO("wave")
#tree<-decisionTree.SDA(sda, "WaveForm~.", testSet=1:30)
#draw.decisionTree.SDA(tree,boxWidth=2,boxHeight=3)