GATE 2025 · session-5
Consider designing a linear binary classifier \(f(x)=\operatorname{sign}(w^Tx+b)\), where \(x\in\mathbb{R}^2\), on the following training data:
\[
\text{Class 1: }\left\{\begin{bmatrix}2\\0\end{bmatrix},\begin{bmatrix}0\\2\end{bmatrix},\begin{bmatrix}2\\2\end{bmatrix}\right\},
\qquad
\text{Class 2: }\left\{\begin{bmatrix}0\\0\end{bmatrix}\right\}.
\]
A hard-margin support-vector machine is solved to obtain \(w\) and \(b\). Which of the following options is/are correct?