Consider the two$-$class classification task that consists of the following $2-$D points:

${}_1$:$(1,1),(2,2),(2,0)$

${}_2$:$(0,0),(1,0),(0,1)$

Using the perceptron algorithm in its reward and punishment form, with $=1$ and

$w(0)=[0,0,0{]}^T,$ demonstrate step$-$by$-$step how to design a linear classifier separating

the two classes.