ALFS is an inductive learning algorithm that employs feature selection to learn concepts from examples. Features which best represent and differentiate a subset from other subsets in learning data are detected and used to produce rules. These rules form a knowledge base for an expert system. The performance of ALFS is illustrated using data sets from the domains of primary tumour and game playing.
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