Maximum likelihood estimation

Maximum Likelihood Estimation
Tutorial Slides by Andrew Moore
MLE is a solid tool for learning parameters of a data mining model. It is a methodlogy which tries to do two things.

MAXIMUM LIKELIHOOD ESTIMATION OF THE
MEAN OF THE EXPONENTIAL DISTRIBUTION
Maximum Likelihood estimation of the mean of the exponential distribution ...

Maximum likelihood estimation. Standard iterative function minimization methods can be used to compute maximum likelihood parameter estimates for the two- and three-parameter Weibull distribution.

Maximum likelihood estimation begins with the mathematical expression known as a likelihood function of the sample data.

Backfitting A method for maximum likelihood estimation of a generalized additive regression. You iteratively optimize each f_i while holding the others fixed. It is equivalent to the Gauss-Seidel method in numerical linear algebra.

The problem was first posed by Ulf Grenander of Brown University in 1977, as a simplified model for maximum likelihood estimation of patterns in digitized images.

See also: Likelihood, Estimation, Distribution, Variance, Data mining