Wyniki wyszukiwania - BazTech

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Analiza i eksploracja danych metodami syntezy logicznej

Łuba Tadeusz, Wąsicki Dariusz

Przegląd Telekomunikacyjny + Wiadomości Telekomunikacyjne

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2020

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nr 1

3--11

PL

W artykule dyskutowane są możliwości zastosowania metod syntezy logicznej w zadaniach eksploracji danych. W szczególności omawiana jest metoda redukcji atrybutów oraz metoda indukcji reguł decyzyjnych. Pokazano, że metody syntezy logicznej skutecznie usprawniają te procedury i z powodzeniem mogą być zastosowane do rozwiązywania ogólniejszych zadań eksploracji danych. W uzasadnieniu celowości takiego postępowania omówiono diagnozowanie pacjentów z możliwością eliminowania kłopotliwych badań.

EN

The article discusses the possibilities of application of logic synthesis methods in data mining tasks. In particular, the method of reducing attributes and the method of inducing decision rules is considered. It is shown that by applying specialized logic synthesis methods, these issues can be effectively improved and successfully used for solving data mining tasks. In justification of the advisability of such proceedings, the patient's diagnosis with the possibility of eliminating troublesome tests is discussed.

2

On Boolean Representation of Continuous Data Biclustering

Michalak Marcin, Ślęzak Dominik

Fundamenta Informaticae

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2019

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Vol. 167, nr 3

193--217

EN

Biclustering is considered as the method of finding two-dimensional subgroups in a matrix of scalars. The paper introduces a new approach to biclustering continuous matrices on the basis of boolean function analysis. We draw the strong relation between inclusion-maximal (maximal with respect to inclusion) biclusters of the assumed maximal difference between the data in a bicluster and prime implicants of a boolean function describing the data. These biclusters are called similarity biclusters. In the opposition to them, a new notion of dissimilarity biclusters was also introduced in the paper.

3

Discretization of data using Boolean transformations and information theory based evaluation criteria

Jankowski C., Reda D., Mańkowski M., Borowik G.

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2015

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Vol. 63, nr 4

923--932

EN

Discretization is one of the most important parts of decision table preprocessing. Transforming continuous values of attributes into discrete intervals influences further analysis using data mining methods. In particular, the accuracy of generated predictions is highly dependent on the quality of discretization. The paper contains a description of three new heuristic algorithms for discretization of numeric data, based on Boolean reasoning. Additionally, an entropy-based evaluation of discretization is introduced to compare the results of the proposed algorithms with the results of leading university software for data analysis. Considering the discretization as a data compression method, the average compression ratio achieved for databases examined in the paper is 8.02 while maintaining the consistency of databases at 100%.

4

Features Reduction Using Logic Minimization Techniques

Borowik G., Łuba T., Zydek D.

International Journal of Electronics and Telecommunications

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2012

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Vol, 58, No. 1

71-76

EN

This paper is dedicated to two seemingly different problems. The first one concerns information theory and the second one is connected to logic synthesis methods. The reason why these issues are considered together is the important task of the efficient representation of data in information systems and as well as in logic systems. An efficient algorithm to solve the task of attributes/arguments reduction is presented.