Given a perceptron model with a heavy$-$side function as its $($hard$)$ activation function for binary classification, its input is a two$-$dimensional data point denoted by $x=[x1,x2{]}^T.$ After learning from the data, the resulting weighted summation function is obtained as $u(x)=-4*x1-3*x2+10.$ The function is plotted as shown below, and two testing data points A and $B$ are plotted too, where $A[1,4{]}^{TT}$; and $B=[-2,2{]}^{TT}.$

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The data point $A,$ if predicted using the model, has a class label of $(0$ or $1$