Motivation: Net Nearest Neighbor Analysis (NNNA) measures a previously unexamined aspect of dinucleotide frequency--the non-compensated, non-repetitive dinucleotides in a sequence...
Utilizing spatial index structures on secondary memory for nearest neighbor search in high-dimensional data spaces has been the subject of much research. With the potential to host...
Christoph Brochhaus, Marc Wichterich, Thomas Seidl
The stochastic discrimination (SD) theory considers learning as building models of uniform coverage over data distributions. Despite successful trials of the derived SD method in s...
Linear Discriminant Analysis (LDA) is a popular feature extraction technique in statistical pattern recognition. However, it often suffers from the small sample size problem when ...
: The k nearest neighbor classification (k-NN) is a very simple and popular method for classification. However, it suffers from a major drawback, it assumes constant local class po...