Families
MP
2015-06-09
> setwd("D:/Dropbox/R/2015-NUS/Session-3/(a) Hierarchical/Family")
> Dataset <-
+ read.table("D:/Dropbox/R/2015-NUS/Session-3/(a) Hierarchical/Family/Families.csv",
+ header=TRUE, sep=",", na.strings="NA", dec=".", strip.white=TRUE)
> scatterplot(y~x, reg.line=FALSE, smooth=FALSE, spread=FALSE,
+ id.method='mahal', id.n = 6, boxplots=FALSE, span=0.5, data=Dataset)
![plot of chunk unnamed-chunk-4 plot of chunk unnamed-chunk-4](data:image/png;base64,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)
1 2 3 4 5 6
1 2 3 4 5 6
> scatterplot(y~x, reg.line=FALSE, smooth=FALSE, spread=FALSE,
+ id.method='mahal', id.n = 6, boxplots=FALSE, span=0.5, data=Dataset)
![plot of chunk unnamed-chunk-5 plot of chunk unnamed-chunk-5](data:image/png;base64,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)
1 2 3 4 5 6
1 2 3 4 5 6
> HClust.1 <- hclust(dist(model.matrix(~-1 + x+y, Dataset)) , method=
+ "single")
> plot(HClust.1, main= "Cluster Dendrogram for Solution HClust.1", xlab=
+ "Observation Number in Data Set Dataset",
+ sub="Method=single; Distance=euclidian")
![plot of chunk unnamed-chunk-6 plot of chunk 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)