Bernard Domanski

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Finding association rules in data that is naturally binary has been well researched and documented. Finding association rules in numeric/categorical data has not been as easy. Many quantitative algorithms work directly on the numeric data limiting the complexity of the generated rules. In addition, as you create intervals from the numeric data the(More)
Analysis of a clinical head trauma dataset was aided by the use of a new, binary-based data mining technique, termed Boolean analyzer (BA), which finds dependency/association rules. With initial guidance from a domain user or domain expert, the BA algorithm is given one or more metrics to partition the entire dataset. The weighted rules are in the form of(More)
KDD (Knowledge Discovery in Databases) is the automated discovery of patterns and relationships in large databases. Data mining is one step in the KDD process. Many data mining algorithms and methods find data patterns using techniques such as neural Analyzer is a data mining method that finds dependency rules of the form X ⇒ Y. Data is Booleanized with(More)