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on Dec 04, 2014 14:25.

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h2. Introduction
Edlin is a collection of machine learning algorithms comprising a large number of state-of-the-art methods for classification and sequence tagging. Even though at their core they are general machine-learning approaches (perceptrons, logistic regression), the implementation is optimized for NLP learning tasks: inputs are represented as sparse document-term matrices, parallel computation is used whenever possible (in order to deal with very large datasets), specific evaluation metrics such as Precision/Recall/F are being reported, appropriate feature selection methods are added in order to reduce dimensionality, etc.

Edlin consists of four sub-projects(Basics, Edlin-Wrapper, Mallet-Wrapper and Feature Extraction) and is closely bound to yet another in-house project, Doc-Classif API(a.k.a DAPI).