Two Projection Pursuit Algorithms for Machine Learning under Non-Stationarity
Machine Learning
2011-10-05 v1 Artificial Intelligence
Abstract
This thesis derives, tests and applies two linear projection algorithms for machine learning under non-stationarity. The first finds a direction in a linear space upon which a data set is maximally non-stationary. The second aims to robustify two-way classification against non-stationarity. The algorithm is tested on a key application scenario, namely Brain Computer Interfacing.
Cite
@article{arxiv.1110.0593,
title = {Two Projection Pursuit Algorithms for Machine Learning under Non-Stationarity},
author = {Duncan A. J. Blythe},
journal= {arXiv preprint arXiv:1110.0593},
year = {2011}
}