Sebastian Stawicki

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We discuss the notion of a decision bireduct [1], which is an extension of the notion of a decision reduct developed within the theory of rough sets. We show relationships between the decision bireducts and some formulations of approximate decision reducts summarized in [2]. We investigate advantages of the decision bireducts and the approximate decision(More)
In this paper we summarize AAIA'14 Data Mining Competition: Key risk factors for Polish State Fire Service which was held between February 3, 2014 and May 5, 2014 at the Knowledge Pit platform http://challenge.mimuw.edu.pl/. We describe the scope and background of this competition and we explain in details the evaluation procedure. We also briefly overview(More)
We investigate how to use the scripts with automatically generated fast-performing analytic SQL statements to speed up the KDD-related tasks of attribute selection and decision tree induction. We base our framework on the entity-attribute-value data model in order to seamlessly scale the required queries with respect to the amounts of attributes involved in(More)
We present a framework for KDD process implemented using SQL procedures, consisting of constructing new attributes, finding rough set-based reducts and inducing decision trees. We focus particularly on attribute reduction, which is important especially for high-dimensional data sets. The main technical contribution of this paper is a complete framework for(More)