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W pracy przedstawiona została metoda warunkowego uzupełniania niekompletnych danych dopełnieniami klas podobieństwa.
The problem of the incomplete data is quite common especially in the case of the actual measurement samples. In this connection, it has been vastly commented in the literaturt, especially in the rough set theory. The rough set theory was meant as a tool for imprecise and inconsistent information systems. The aim of this work is to supplement the incomplete data relying on the relations designed to this problem, (similarity and tolerance relation). Basing on the opposite information to the incomplete object we know the area of permitted values for this object. The method proposed in the article works on the assumption that we possess with the opposite information to the supplemented sample in our information system.
Content available remote Incomplete measurement data in the problem of classification
In the article the author has attempted to supplement, the incomplete measurement samples with an introductory analysis of the profitability of the possible prediction of the missing values. In order to do that a fuzzy model, automatically tuned by a self-organising neural network, has been applied. Thus, the method may be used for solving problems connected with classification. However, the idea of treating the incomplete data has been adopted from the rough set theory.
Content available remote A system for behavioral therapy support for autistic children
The Applied Behavioral Analysis (ABA) is one of the very successful therapies on autistic children. There are no software systems supporting such a complex therapy either in Polish or international ABA rehabilitation centers. This article presents an idea of an integrated system to help managing the vast amount of data collected during behavioral therapy. There are four main modules in the system: a database containing therapy data, system for data analysis based on machine learning techniques, an expert system to support therapist and a semantic based search.
Stosowana analiza behawioralna jest jedną ze skuteczniejszych terapii dla dzieci z autyzmem. Zarówno w Polskich jak i światowych centrach rehabilitacyjnych nie stosuje się systemów oprogramowania, które wspierałby tą skomplikowaną terapię. Niniejszy artykuł prezentuje ideę zintegrowanego systemu wspomagającego zarządzenie ogromną ilością danych gromadzonych podczas terapii. W systemie zaplanowano cztery moduły: bazę danych zawierającą dane z terapii, system analizy danych wykorzystujący techniki z maszynowego uczenia się, system ekspertowy dla terapeutów oraz oparty na semantyce.
In this paper we present a theorem concerning an equivalent statement of the Jacobian Conjecture in terms of Picard-Vessiot extensions. Our theorem completes the earlier work of T. Crespo and Z. Hajto which suggested an effective criterion for detecting polynomial automorphisms of affine spaces. We show a simplified criterion and give a bound on the number of wronskians determinants which we need to consider in order to check if a given polynomial mapping with non-zero constant Jacobian determinant is a polynomial automorphism. Our method is specially efficient with cubic homogeneous mappings introduced and studied in fundamental papers by H. Bass, E. Connell, D.Wright and L. Drużkowski.
Content available remote Significance of condition attributes in child well-being analysis
In this study the significance of attributes in child well-being is presented. The main goal was to find features most specific for child-well being evaluation in Poland. The dataset was obtained from a survey based on a special questionnaire. To select important attributes three filter for individual attribute rank were used ?2, information gain and relief attribute evaluator and one filter-subset selector based on rough set theory. In the article the dataset is described in details. All the attributes are named, divided by category and for each a domain is given. Then methods of attribute selection applied in experiments are presented. Finally results on selecting attributes relevant for child well-being are discussed.
The aim of the article is to establish a list of capabilities with reference to children’s well being in Poland. This issue can be considered as a multicriterial classification problem where decision attributes classes are ordered due to the preference – criteria. We used a Dominance-based Rough Set Approach (DRSA) adapted to deal with missing values. Analysis was performed on data set collected in Zachodniopomorskie district as a result of survey conduction.
The aim of this research was to induct rules from a dataset obtained through a survey on child well-being that was performed in Poland Western Pomarania. For rule induction the exhaustive algorithm was used. The assessment of the strengths of found rules can be carried out and expressed in terms of: the conditional entropy and the Kullback-Leibler's number. Resulting rules are elements of a Pareto optimal set of derived rules, which are 'sensible' and 'interesting', Each rule combines thefunctionings (activities during childhood) and subjective evaluation of childhood.
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