Finding input sub-spaces for Polymorphic Fuzzy Signatures
A significant feature of fuzzy signatures is its applicability for complex and sparse data. To create Polymorphic Fuzzy Signatures (PFS) for sparse data, sparse input sub-spaces (ISSs) should be considered. Finding the optimal ISSs manually is not a simple task as it is time consuming; moreover, some knowledge about the dataset is necessary. Fuzzy C-Means (FCM) clustering employed with a trapezoidal approximation method is needed to find ISSs automatically. Furthermore, dealing with sparse...[Show more]
|Collections||ANU Research Publications|
|Source:||Proceedings of the 18th international conference on Fuzzy Systems|
|01_Hadad_Finding_input_sub-spaces_for_2009.pdf||1.56 MB||Adobe PDF||Request a copy|
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