Abstract
A new theoretical framework for the analysis of linear combiners is presented in this paper. This framework extends the scope of previous analytical models, and provides some new theoretical results which improve the understanding of linear combiners operation. In particular, we show that the analytical model developed in seminal works by Tumer and Ghosh is included in this framework.
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Biggio, B., Fumera, G., Roli, F. (2007). Bayesian Analysis of Linear Combiners. In: Haindl, M., Kittler, J., Roli, F. (eds) Multiple Classifier Systems. MCS 2007. Lecture Notes in Computer Science, vol 4472. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72523-7_30
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DOI: https://doi.org/10.1007/978-3-540-72523-7_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72481-0
Online ISBN: 978-3-540-72523-7
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