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Bayesian Reasoning and Machine Learning by David Barber

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Figure 14.1 In nearest neighbour classification a new vector is assigned the label of the nearest vector in the training set. Here there are three classes, with training points given by the circles, along with their class. The dots indicate the class of the nearest training vector. The decision boundary is piecewise linear with each segment corresponding to the perpendicular bisector between two datapoints belonging to different classes, giving rise to a Voronoi tessellation of the input space-

Figure 16.3 (a) Canonical variates projection of examples ...

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