Consider the following set of data points:

input

x$1$ x$2$

desired label

$10$

$1$

$01$

$1$

$-10$

$0$

$-11$

$0$

$0-1$

$0$

As the above table shows, the data points are categorized $($labeled$)$ into two groups specified by the labels $1$ and $0.$

$($A$)$ Use the perceptron learning rule to train a single$-$neuron perceptron on the data points given above. Initialize the weights to $($w$0=-0\mathrm{.}7,$ w$1=-0\mathrm{.}2,$ w$2=0\mathrm{.}95),$ assume the learning rate is $1,$ and use the hard$-$limiter activation function $($If output $1$; otherwise output $0),$ i$.$e$.$:

image.png

Report the weights after one iteration w$0=$

w$1=$

w$2=$

Report the weights after two iterations w$0=$

w$1=$

w$2=$

$.$ NOTE: Report them in x$.$xx format.