[Solved] ECE472, Deep Learning Assignment 2

Problem Statement Consider a set of examples with two classes and distributions as

in Figure 1. Given the vector x R² infer its target class t {0,1}. As a model 011 use a multi-layer perceptron f which returns an estimate for the conditional ⁰¹² density p(t = 1 | x):

2

f : R [0,1] (1)

parametrisized by some set of values . All of the examples in the training set

should be classified correctedly (i.e. p(t = 1 x) > 0.5 if and only if t = 1).

Impose an L² penalty on the set of parameters. Produce one plot. Show the

examples and the boundary corresponding to p(t = 1 | x) = 0.5. The plot must be

of suitable visual quality. It may be difficult to to find an appropriate functional

form for f, write a few sentences discussing your various attempts.