Kernel Feature Selection via Conditional Covariance Minimization

NeurIPS 2017 Jianbo ChenMitchell SternMartin J. WainwrightMichael I. Jordan

We propose a method for feature selection that employs kernel-based measures of independence to find a subset of covariates that is maximally predictive of the response. Building on past work in kernel dimension reduction, we show how to perform feature selection via a constrained optimization problem involving the trace of the conditional covariance operator... (read more)

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