Logistic Regression
Logistic regression is a model used for prediction of the probability of occurrence of an event. It makes use of several predictor variables that may be either numerical or categories.
Logistic regression is the discrimitive equivalent to naive bayes. It does not model the probability of the input data (p( x )) as naive bayes does. Accordingly it cannot make false assumptions on the distribution of the input data, as is done in naive bayes.
For a more detailed analysis of the approach, have a look at the thesis of Paul Komarek:
