André Pilastri
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Learning Kernels for Support Vector Machines with Polynomial Powers of Sigmoid
In the pattern recognition research field, Support Vector Machines (SVM) have been an effectiveness tool for classification purposes, being successively employed in many applications. The SVM input data is transformed into a high dimensional space …
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