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