000 ece, Selected Topics in Machine Learning – Assignment 2
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004 tldr: Perform binary classification on the spirals dataset using a multi-layer 005 perceptron. You must generate the data yourself.
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008 Problem Statement Consider a set of examples with two classes and distributions as
009010 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):
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014 f : R → [0,1] (1)
015 parametrisized by some set of values θ. All of the examples in the training set
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should be classified correctedly (i.e. p(t = 1 x) 0.5 if and only if t = 1).
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018 Impose an L2 penalty on the set of parameters. Produce one plot. Show the
019 examples and the boundary corresponding to p(t = 1 | x) = 0.5. The plot must be
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021 of suitable visual quality. It may be difficult to to find an appropriate functional 022 form for f, write a few sentences discussing your various attempts.
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037 −5
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040 −10
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043 −15
044 −10 −5 0 5 10
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046 Figure 1: Sample spiral data.
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