A Theoretical Analysis of Feature Fusion in Stacked Generalization

Date

2009-04-11

Author

Ozay, Mete
Yarman Vural, Fatoş Tunay

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In the present work, a theoretical framework in order to define the general performance of stacked generalization learning algorithm is developed. Analytical relationships between the performance of the Stacked Generalization classifier relative to the individual classifiers are constructed by the proposed theorems and the practical techniques are developed in order to optimize the performance of stacked generalization algorithm based on these relationships.

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https://hdl.handle.net/11511/53537

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Department of Computer Engineering, Conference / Seminar

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Citation Formats

M. Ozay and F. T. Yarman Vural, “A Theoretical Analysis of Feature Fusion in Stacked Generalization,” 2009, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/53537.