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stat.ML2009
The Feature Importance Ranking Measure
Alexander Zien, Nicole Kraemer, Soeren Sonnenburg +1
Most accurate predictions are typically obtained by learning machines with complex feature spaces (as e.g. induced by kernels). Unfortunately, such decision rules are hardly access…
stat.ML2009★ 3 cited
Lanczos Approximations for the Speedup of Kernel Partial Least Squares Regression
Nicole Kraemer, Masashi Sugiyama, Mikio Braun
The runtime for Kernel Partial Least Squares (KPLS) to compute the fit is quadratic in the number of examples. However, the necessity of obtaining sensitivity measures as degrees o…