In this letter, we comment on "Pruning Error Minimization in Least Squares Support Vector Machines"by B. J. de Kruif and T. J. A. de Vries. The original paper proposes a way of pruning training examples for least squares support vector machines (LS SVM) using no regularization (? = 8). This causes a problem as the derivation involves inverting a matrix that is often singular. We discuss a modification of this algorithm that prunes with regularization (? finite and nonzero) and is also computationally more efficient. © 2007 IEEE.
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