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**Algorithms for maximum-likelihood logistic regression**

**Thomas P. Minka**

### Abstract:

Logistic regression is a workhorse of statistics and is closely related to
methods used in Machine Learning, including the Perceptron and the
Support Vector Machine. This note reviews seven different algorithms for
finding the maximum-likelihood estimate. Iterative Scaling is shown to
apply under weaker conditions than usually assumed. A modified iterative
scaling algorithm is also derived, which is equivalent to the algorithm of
Collins et al (2000). The best performers in terms of running time are the
line search algorithms and Newton-type algorithms, which far outstrip
Iterative Scaling.

*Heidi Sestrich*

*10/19/2001*
Here is the pdf file for this
technical report.