GATE 2026 Data Science & AI Q55

Question

Consider that Linear Ridge Regression is being used to learn a prediction function y_pred = w^T x, where w, x ∈ R^2 and Mean Absolute Error (MAE) is used to measure the prediction error. A weight of 0.20 is associated with the regularizer.
At an intermediate step of the training process, assume that the parameter w = [-3.00, 4.00]^T. In the next step, for the input x = [1.00, 2.00]^T, the predicted value of y is noted. Let the relation between x = [x1, x2]^T and the true value of y be y_true = x1 + x2.
The value of the overall regularized loss function for this instance is _________.
(Rounded off to two decimal places)

Accepted Answer

6.90 to 7.10