Discovering Patterns in EEG-Signals: Comparative Study of a Few Methods
暂无分享，去创建一个
The objective of this paper is to draw the attention of the ML-researchers to the domain of data analysis. The issue is illustrated by an attractive case study—automatic classification of non-averaged EEG-signals. We applied several approaches and obtained best results from a combination of an ID3-like program with Bayesian learning.
[1] Tim Niblett,et al. Constructing Decision Trees in Noisy Domains , 1987, EWSL.
[2] Gert Pfurtscheller,et al. Brain-computer interface: a new communication device for handicapped persons , 1993 .
[3] Teuvo Kohonen,et al. The self-organizing map , 1990 .
[4] Geoffrey E. Hinton,et al. Learning internal representations by error propagation , 1986 .
[5] Jude W. Shavlik,et al. Constructive Induction in Knowledge-Based Neural Networks , 1991, ML.