Determination of the Mahalanobis matrix using nonparametric noise estimations

In this paper, the problem of an optimal transformation of the input space for function approximation problems is addressed. The transformation is defined determining the Mahalanobis matrix that minimizes the variance of noise. To compute variance of the noise, a nonparametric estimator called the Delta Test paradigm is used. The proposed approach is illlustrated on two different benchmarks.

• Type: Conference
• Year: 2006
• Where: ESANN
• Authors: Amaury Lendasse, Francesco Corona, Jin Hao, Nima Reyhani, Michel Verleysen
• Keywords: Delta Test Paradigm, ESANN 2006, ESANN 2007, Function Approximation Problems, Optimal Transformation