A machine learning classifier, directed at text categorization. #Machine learning tool #Maximum entropy classifier #Machine learning classifier #Machine #Learn #Entropy
Stanford Classifer is a free and open-source machine learning tool that will take data items and place them into one of k classes. A probabilistic classifier, like this one, can also give a probability distribution over the class assignment for a data item.
Stanford Classifer is a Java implementation of a maximum entropy classifier. Maximum entropy models are otherwise known as conditional loglinear models, and are essentially equivalent to multiclass logistic regression models (though parameterized slightly differently, in a way that is advantageous with sparse explanatory feature vectors).
Detailed instructions on how to install and use the Stanford Classifer utility on your Mac are available HERE.
Stanford Classifer is a cross-platform utility capable of running on any operating system that comes with Java support (e.g. Mac OS X, Windows, Linux).
System requirements
Stanford Classifer 2.1.4
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