Typically discretisation procedures are implemented as a part of initial pre-processing of data, before knowledge mining is employed. It means that conclusions and observations are based on reduced data, as usually by discretisation some information is discarded. The paper presents a different approach, with taking advantage of discretisation executed after data mining. In the described study firstly decision rules were induced from real-valued features. Secondly, data sets were discretised. Using categories found for attributes, in the third step conditions included in inferred rules were translated into discrete domain. The properties and performance of rule classifiers were tested in the domain of stylometric analysis of texts, where writing styles were defined through quantitative attributes of continuous nature. The performed experiments show that the proposed processing leads to sets of rules with significantly reduced sizes while maintaining quality of predictions, and allows to test many data discretisation methods at the acceptable computational costs.
The present paper describes the problem and effects of water scarcity and the possibility of rational use of this resource in the idea of a Circular Economy (CE) and sustainable development. Rational water management requires innovation, due to the growing demand for this raw material. It seems that water is widely available, e.g., in Poland, there is no problem with drought. Unfortunately, Polish water resources are shrinking and modern solutions, as well as the construction of new and modernisation of old infrastructure, are some of the few solutions that can protect against a shortage of potable water. Water is also an essential resource for economic development. It is used in every sector of the economy. Limited water resources lead to an inevitable energy transformation because, in its present state, the Polish energy industry consumes huge amounts of water. Due to the above statements, the authors propose a solution in the form of an interactive shower panel that contributes to more rational water management (e.g., in households or hotels) based on the latest technological achievements. This device enables the creation of water consumption statistics based on accurate liquid flow measurements and the transfer of data to the user’s mobile device. This innovation aims to make the user aware of the amount of water used, which in turn can contribute to lower water consumption.
Abstract. The presented paper addresses problem of evaluation of decision systems in authorship attribution domain. Two typical approaches are cross-validation and evaluation based on specially created test datasets. Sometimes preparation of test sets can be troublesome. Another problem appears when discretization of input sets is taken into account. It is not obvious how to discretize test datasets. Therefore model evaluation method not requiring test sets would be useful. Cross-validation is the well-known and broadly accepted method, so the question arose if it can deliver reliable information about quality of prepared decision system. The set of classifiers was selected and different discretization algorithms were applied to obtain method invariant outcomes. The comparative results of experiments performed using cross-validation and test sets approaches to system evaluation, and conclusions are presented.
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