Markov Blanket Ranking using Kernel-based Conditional Dependence Measures

1 Feb 2014Eric V. StroblShyam Visweswaran

Developing feature selection algorithms that move beyond a pure correlational to a more causal analysis of observational data is an important problem in the sciences. Several algorithms attempt to do so by discovering the Markov blanket of a target, but they all contain a forward selection step which variables must pass in order to be included in the conditioning set... (read more)

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