Induction of formal concepts by lattice computing techniques for tunable classification
Induction of formal concepts by lattice computing techniques for tunable classification is a scholarly work, published in 2014 in ''Journal of Engineering Science and Technology Review''. The main subjects of the publication include formal specification, Galois connection, classifier, lattice, data mining, formal concept analysis, artificial intelligence, Type-2 fuzzy sets and systems, Lattice Miner, artificial neural network, theoretical computer science, Formal, formal methods, machine learning, rough set, formal language, and computer science. The work proposes an enhancement of Formal Concept Analysis (FCA) by Lattice Computing (LC) techniques.More specifically, a novel Galois connection is introduced toward defining tunable metric distances as well as tunable inclusion measure functions between formal concepts induced from hybrid (i.e., nominal and numerical) data.An induction of formal concepts is pursued here by a novel extension of the Karnaugh map, or K-map for short, technique from digital electronics.In conclusion, granular classification can be pursued.The capacity of a classifier based on formal concepts is demonstrated here with promising results.The formal concepts are interpreted as descriptive decisionmaking knowledge (rules) induced from the training data.