The Nearest Neighbor Algorithm - Classes

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Decision Boundaries

With large number of examples

and possible noise in the labels,

the decision i boundary can

become nasty!

We end up overfitting the data

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Decision Boundaries: The Voronoi Diagram • Decision boundaries are formed by a subset of the Voronoi diagram of the training data • Each line segment is equidistant between two points of opposite class. • The more examples that are p stored, the more fragmented and complex the decision boundaries can become.

Decision Boundaries With large number of examples and possible noise in the labels, the decision i boundary can become nasty! We end up overfitting the data

Page 1 and 2: The Nearest Neighbor Algorithm •
Page 3: Decision Boundaries: The Voronoi Di
Page 7 and 8: Effect of K K=1 K=15 Figures from H
Page 9 and 10: Distance Weighted Nearest Neighbor
Page 11 and 12: The Curse of Dimensionality: Illust
Page 13 and 14: Curse of Noise (2) Location of x 1
Page 15: Nearest Neighbor Summary • Advant

The Nearest Neighbor Algorithm - Classes

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