Topology of strings: median string is NP-complete
Theoretical Computer Science
Fast Computation of Normalized Edit Distances
IEEE Transactions on Pattern Analysis and Machine Intelligence
Median strings for k-nearest neighbour classification
Pattern Recognition Letters
Fast Median Search in Metric Spaces
SSPR '98/SPR '98 Proceedings of the Joint IAPR International Workshops on Advances in Pattern Recognition
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
A Stochastic Approach to Median String Computation
SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Image and Vision Computing
Pattern Recognition Letters
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The k-Nearest Neighbour (k-NN) rule is one of the most popular techniques in Pattern Recognition. This technique requires good prototypes in order to achieve good results with a reasonable computational cost. When objects are represented by strings, the Median String of a set of strings could be the best prototype for representing the whole set (i.e., the class of the objects). However, obtaining the Median String is an NP-Hard problem, and only approximations to the median string can be computed with a reasonable computational cost. Although proposed algorithms to obtain approximations to Median String are polynomial, their computational cost is quite high (cubic order), and obtaining the prototypes is very costly. In this work, we propose several techniques in order to reduce this computational cost without degrading the classification performance by the Nearest Neighbour rule.