FTL is a library to represent knowledge using the Feature Term formalism. It supports the creation of ontologies, and the basic operations with feature terms: subsumption, antiunification and unification. Additionally, it implements a collection of refinement operators which can be used as the basis of many learning and reasoning algorithms.

As a bonus, fterm comes with a collection of learning algorithms already coded as examples: similarity evaluations, FOIL (HIDRA), LID, INDIE, ABUI, AMAIL, and also a package to perform argumentation using feature terms. Translators from terms to other formats such as Horn Clauses, or even LaTeX figures are also included.

Finally, a collection of datasets represented as feature terms is included (most from the UCI machine learning repository). Find them in the NOOS subfolder

The library was developed by Santiago Ontañón in collaboration with Enric Plaza, and with contributions by Carlos López del Toro.


Copyright (c) 2013, Santiago Ontañón All rights reserved.

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