Preprocessing with Linear Transformations that Maximize the Nearest Neighbor Classification Accuracy

Mehmet Ali Yatbaz and Deniz Yuret. 1st CSE Student Workshop (CSW’10), 21 February 2010, Koc Istinye Campus, Istanbul. (PDF, PPT)

Abstract
We introduce a preprocessing technique for classification problems based on linear transformations. The algorithm incrementally constructs a linear transformation that maximizes the nearest neighbor classification accuracy on the training set. At each iteration the algorithm picks a point in the dataset, and computes a transformation
that moves the point closer to points in its own class and/or away from points in other classes. The composition of the resulting linear transformations lead to statistically significant improvements in instance based learning algorithms.



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