Multistage Naive Bayes Classifier with Reject Option for Multiresolution Signal Representation

Urszula Libal

2013

Abstract

In the article, two approaches to pattern recognition of signals are compared: a direct and a multistage. It is assumed that there are two generic patterns of signals, i.e. a two-class problem is considered. The direct method classifies signal in one step. The multistage method uses a multiresolution representation of signal in wavelet bases, starting from a coarse resolution at the first stage to a more detailed resolutions at the next stages. After a signal is assigned to a class, the posterior probability for this class is counted and compared with a fixed level. If the probability is higher than this level, the algorithm stops. Otherwise the signal is rejected and on the next stage the classification procedure is repeated for a higher resolution of signal. The posterior probability is calculated again. The algorithm stops when the probability is higher than a fixed level and a signal is finally assigned to a class. The wavelet filtration of signal is used for feature selection and acts as a magnifier. If the posterior probability of recognition is low on some stage, the number of features on the next stage is increased by taking a better resolution. The experiments are performed for three local decision rules: naive Bayes, linear and quadratic discriminant analysis.

References

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  8. Figure 5: Risk for naive Bayes classifier.
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Paper Citation


in Harvard Style

Libal U. (2013). Multistage Naive Bayes Classifier with Reject Option for Multiresolution Signal Representation . In Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-8565-41-9, pages 289-292. DOI: 10.5220/0004266002890292


in Bibtex Style

@conference{icpram13,
author={Urszula Libal},
title={Multistage Naive Bayes Classifier with Reject Option for Multiresolution Signal Representation},
booktitle={Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2013},
pages={289-292},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004266002890292},
isbn={978-989-8565-41-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Multistage Naive Bayes Classifier with Reject Option for Multiresolution Signal Representation
SN - 978-989-8565-41-9
AU - Libal U.
PY - 2013
SP - 289
EP - 292
DO - 10.5220/0004266002890292