Logistic regression is probably responsible for the majority of industrial classifiers, with the possible exception of naïve Bayes classifiers. It almost certainly is one of the best performing classifiers available, albeit at the cost of slow training and considerable complexity in configuration and tuning.

Logistic regression is also known as maximum entropy, neural network classification with a single neuron, and others. So far in this book, the classifiers have been based on the underlying characters or tokens, but logistic regression uses unrestricted feature extraction, which allows for arbitrary observations of the situation to be encoded in the classifier.

This recipe closely follows a more complete tutorial at http://alias-i.com/lingpipe/demos/tutorial/logistic-regression/read-me.html.