Abstract
Knowledge discovery from databases is a very attractive and challenging task. The elicitation of fuzzy predicates (called FuzzyPred) in conjunctive and disjunctive normal form provides a convenient and effective general way to identify and to represent certain dependencies among items in fuzzy transactions. Konstanz Information Miner (KNIME) is a strong and comprehensive free platform for drag-and-drop analytics, machine learning, statistics, and data processing. It already offers a large variety of nodes, which enables easy execution of data pipelines. This paper presents a new plug-in that integrates FuzzyPred into KNIME. It allows reducing the amount of knowledge and experience required by users to use the method. A case of study is given to illustrate the use of the proposal.
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