Kernel regression
Technique in statistics / From Wikipedia, the free encyclopedia
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Not to be confused with Kernel principal component analysis or Kernel ridge regression.
In statistics, kernel regression is a non-parametric technique to estimate the conditional expectation of a random variable. The objective is to find a non-linear relation between a pair of random variables X and Y.
In any nonparametric regression, the conditional expectation of a variable relative to a variable may be written:
where is an unknown function.