--R Package 'smbinning': Optimal Binning for Scoring Modeling(http://blog.revolutionanalytics.com/2015/03/r-package-smbinning-optimal-binning-for-scoring-modeling.html)

library(smbinning) 
data(chileancredit) 
# Training and testing samples 
chileancredit.train=subset(chileancredit,FlagSample==1) 
chileancredit.test=subset(chileancredit,FlagSample==0) 

# Run and save results 
result=smbinning(df=chileancredit.train,y="FlagGB",x="TOB",p=0.05) 
result$ivtable

# Relevant plots (2x2 Page) 
par(mfrow=c(2,2)) 
boxplot(chileancredit.train$TOB~chileancredit.train$FlagGB, 
horizontal=T, frame=F, col="lightgray",main="Distribution") 
mtext("Time on Books (Months)",3) 
smbinning.plot(result,option="dist",sub="Time on Books (Months)") 
smbinning.plot(result,option="badrate",sub="Time on Books (Months)") 
smbinning.plot(result,option="WoE",sub="Time on Books (Months)")
par(mfrow=c(1,1))