Growing some Trees

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Consider here the dataset used in a previous post, about visualising a classification (with more than 2 features), > MYOCARDE=read.table( + "http://ift.tt/1Ew09Qc;, + header=TRUE,sep=";") The default classification tree is > arbre = rpart(factor(PRONO)~.,data=MYOCARDE) > rpart.plot(arbre,type=4,extra=6) We can change the options here, such as the minimum number of observations, per node > arbre = rpart(factor(PRONO)~.,data=MYOCARDE, + control=rpart.control(minsplit=10)) > rpart.plot(arbre,type=4,extra=6) or > arbre = rpart(factor(PRONO)~.,data=MYOCARDE, + control=rpart.control(minsplit=5)) > rpart.plot(arbre,type=4,extra=6) To visualize that classification, use the following code (to get a projection on the first two components) … Continue reading Growing some Trees →

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