In statistics, generalized iterative scaling (GIS) and improved iterative scaling (IIS) are two early

algorithm In mathematics and computer science, an algorithm () is a finite sequence of rigorous instructions, typically used to solve a class of specific problems or to perform a computation. Algorithms are used as specifications for performing ...

s used to fit

log-linear model A log-linear model is a mathematical model that takes the form of a function whose logarithm equals a linear combination of the parameters of the model, which makes it possible to apply (possibly multivariate) linear regression. That is, it h ...

s, notably

multinomial logistic regression In statistics, multinomial logistic regression is a statistical classification, classification method that generalizes logistic regression to multiclass classification, multiclass problems, i.e. with more than two possible discrete outcomes. T ...

(MaxEnt) classifiers and extensions of it such as MaxEnt Markov models and

conditional random field Conditional random fields (CRFs) are a class of statistical modeling methods often applied in pattern recognition and machine learning and used for structured prediction. Whereas a classifier predicts a label for a single sample without consi ...

s. These algorithms have been largely surpassed by gradient-based methods such as

L-BFGS Limited-memory BFGS (L-BFGS or LM-BFGS) is an optimization algorithm in the family of quasi-Newton methods that approximates the Broyden–Fletcher–Goldfarb–Shanno algorithm (BFGS) using a limited amount of computer memory. It is a popular alg ...

and

coordinate descent Coordinate descent is an optimization algorithm that successively minimizes along coordinate directions to find the minimum of a function. At each iteration, the algorithm determines a coordinate or coordinate block via a coordinate selection rule, ...

algorithms.

References

Optimization algorithms and methods Log-linear models {{statistics-stub

See also

References