Abstract
Expanding the training dataset is a new technique proposed recently to improve the performance of classification methods. In this paper, we propose a powerful method to conduct the previous task. Our method is based on applying the Bayesian test based on emerging patterns to evaluate and improve the quality of the new data instances used to expand the training data space. Our experiments on a number of datasets show that our method outperforms the previous proposed methods and is able to add additional knowledge to the space of data.
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Alhammady, H. (2007). Expanding the Training Data Space Using Bayesian Test. In: Elleithy, K. (eds) Advances and Innovations in Systems, Computing Sciences and Software Engineering. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-6264-3_28
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DOI: https://doi.org/10.1007/978-1-4020-6264-3_28
Publisher Name: Springer, Dordrecht
Print ISBN: 978-1-4020-6263-6
Online ISBN: 978-1-4020-6264-3
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