R d3netwrok sample using randomForest proximity of mtcars

#-----[ unsupervised proximity in rf ] --------

data(mtcars)

crf1 <- randomForest(mpg ~ ., data=mtcars, 

      importance=TRUE,  proximity=TRUE)

m1 <- melt(crf1$proximity)

plot(sort(m1$value))

#--- make a graph using RF proximity --------

# install.packages("d3Network")

require(d3Network)

m2 <- m1[m1$value>quantile(m2$value,0.7) & m1$value<1,]

NetworkData <- data.frame(m2$X1, m2$X2, m2$value)

# create an html file presenting grpah

d3SimpleNetwork(NetworkData, width = 400, height = 400, file = "d3netofRFpox1.html")

#----[ importance and error scatter plot ]---

plot(crf1, log="y")

rfvimpdf<- as.data.frame(crf1$importance)

# error and purity combined

rfvimpdf$epcm<- (rfvimpdf[,1]/max(rfvimpdf[,1]) ) *(rfvimpdf[,2]/max(rfvimpdf[,2]) )

# coldf[colnum==23,] 

plot(rfvimpdf[,1:2],  main="randomForest var Importance", pch=20, cex=2, col= ifelse(rfvimpdf$epcm > quantile(rfvimpdf$epcm,0.7) , rgb( 0, 139, 139, maxColorValue=255), rgb( 139, 125, 107, maxColorValue=255) ))  

text(rfvimpdf[,1:2], labels=row.names(rfvimpdf), pos=3)

lines(c(NA,NA,NA,NA,NA,max(rfvimpdf[,2]) *6/6,  max(rfvimpdf[,2]) *6/7,  max(rfvimpdf[,2]) *6/8, max(rfvimpdf[,2]) *6/9, max(rfvimpdf[,2])*6/10, max(rfvimpdf[,2]) *6/11 ), lst=2)

# insert grid line in the plot

grid(5,5)