Implementation of supervised learning via R

As we have discussed in the previous chapter, the best choice to conduct various tests for supervised learning is applying an R package called Rattle. Here, we show two more examples. Let's first look at the iris dataset:

> library(rattle) 
> rattle() 

The next example is using the diabetes dataset, shown in the screenshot here:

For example, we could choose the logistic model after clicking Model on the menu bar. After clicking on Execute, we would have the following output:

Based on the significant level of p-values, we could see that in addition to the intercept, x1, x2, x3, and x6 are statistically significant.

The next example is from the R package called LogicReg. The code is given here:

library(LogicReg) 
data(logreg.testdat) 
y<-logreg.testdat[,1] 
x<-logreg.testdat[, 2:21] 
n=1000 
n2=25000 
set.seed(123) ...