Markup : # Calculating Error Function #

Markup : We have a dataset of 40 training examples. Markup : The i-th training example is denoted as (xi, ti), where xi is the example input and ti is the target output. Markup : The target inputs xi can be downloaded from training_inputs1.txt. Markup : Each xi is a three-dimensional vector denoted as (xi, 1, xi, 2, xi, 3). Markup : In file training_inputs1.txt, the number at row i and column j is the value for xi, j. Markup : The target outputs ti can be downloaded from training_outputs1.txt. Markup : Each ti is a real number. Row i of training_outputs1.txt contains the value for ti.

Markup : Error Function formula Markup : 

Markup : Let w be a three dimensional vector (w1, w2, w3). Markup : Define y(xi, w) as follows: y(xi, w) = w1 * xi, 1 + w2 * xi, 2 + w3 * xi, 3. Markup : Part a: If w = (3, -1.5, -2), evaluate E(w) Markup : Part b: If w = (5.2, -2, 1), evaluate E(w)

Markup : Regularisation formula Markup : 

Markup : Part c: If w = (3, -1.5, -2) and ? = 0.25, evaluate the alternative error
Markup : Part d: If w = (5.2, -2, 1) and ? = 0.25, evaluate the alternative error