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We discuss how the specifics of data granulation methodology can influence Infobright's database system performance. We put together our two previous research paths related to machine-generated data sets, namely, dynamic reorganization of data during load and efficient handling of alphanumeric columns with compound values. We emphasize the role of domain knowledge while tuning data granulation processes.
Nowadays, multi-label classification methods are of growing interest. Due to the relationships among the labels, traditional single-label classification methods are not directly applicable to the multi-label classification problem. This paper presents a novel multi-label classification framework based on the variable precision neighborhood rough sets, called Multi-Label classification using Rough...
Centroids are a common defuzzification method for fuzzy sets defined on the real line, and thus are practically important in type-1 and type-2 fuzzy logic systems. We propose a modified definition of the centroid that takes account of singleton spikes in membership. Such spikes are encountered in aggregates that combine fuzzy sets whose support is discrete with fuzzy sets whose support is defined...
Quality characteristics are often imperfect (incomplete, censored, vague or partially unknown) in representing the quality information about products or services. Such imperfectness sometimes may be well described in vague, imprecise or linguistic way. In practice the LR-fuzzy number data are frequently recommended to be used in above cases. LR-fuzzy number itself can be generated with method of Cheng...
Certain advantages of midpoint/radius notation for boxes are well known. Box notation, a concise midpoint/radius scheme employing a ‘box operator’, ϖ, significantly simplifies box calculations. The box math approach to interval analysis, emphasizing ‘image-centered’ representations and assessment of quality of approximation, demonstrates the power of mid-point/ radius methods. A prime example is the...
We study higher order Takagi-Sugeno fuzzy systems from the point of view of their approximation capability. Higher order Takagi-Sugeno fuzzy systems have the output of each individual rule defined as polynomials of a certain degree. In the present paper the individual rule outputs are Taylor polynomials. Under very relaxed conditions both on the target function and the fuzzy sets in the antecedent...
Fuzzy models offer a convenient way to describe complex and nonlinear systems. Fuzzy relational equations, viewed as a certain class of fuzzy models, play a pivotal role in fuzzy modeling. Their theory supports ways in which these equations could be solved and offers a characterization of the resulting families of solutions. Assuming that the corresponding relational equation or a system of relational...
Automatized classification of jewelry stones according to their quality is performed by means of image processing. In this contribution, we discuss a preprocessing of the classification. Several methods of producing a visual representation of jewelry stones are analyzed. Finally, a comparison of the proposed methods and experiments with graphical outputs are given.
In multi-criteria decision analysis problems, attributes are criteria with preference-ordered scales and the decision classes are also preference-ordered. Dominance-based rough set approach is an extension of classic rough set approach, which taking into account the ordering properties of criteria. Set-valued decision system is a generalized model of single-valued decision system. Knowledge from decision...
Any conceptual computer or computing with words (CW) system is expected to represent its results with a reasonable output, such as a sentence in natural language. A CW system is required to translate the fuzzy values provided as its result into words. This paper explores different similarity measures as well as linguistic approximation methods for generating natural language sentences for CW systems...
In this paper, we propose three outlier detection approaches for the fuzzy regression models proposed by Tanaka after a brief review of the related literatures. Generally speaking, for the upper regression model, the aim is to pick out some abnormal data that is not consistent with the trend of the upper regression model; for the lower regression model, as it often has no feasible solutions, the efforts...
This paper investigates rough clustering of objects from uncertain databases using possibility and rough set theories. Real databases can contain both certain and uncertain attribute values. To properly cluster such instances into different clusters, it is necessary to take into account such uncertainty. When clustering objects with uncertain values, we have to consider the similarities between each...
Cost-sensitive learning is both hot and difficult in data mining and machine learning applications. Some research considers only one type of cost. Others convert two or more types of cost into the same unit, and then deal with a single-objective optimization problem. However, in many cases different types of cost cannot be converted. In this paper, we define and tackle multi-objective attribute reduct...
The model of decision-theoretic shadowed sets provides a cost-sensitive approach to three-valued approximation of a fuzzy set on a finite universe. We introduce a semantic meaningful objective function for modeling shadowed sets using the decision theory. This paper is an extension and generalization of the decision-theoretic shadowed sets. We improve the cost-sensitive approach by generalizing the...
The evaluation of Resort Management System (RMS) quality is an item of many trials. We propose applying a complex system of two control algorithms to provide a final estimation of RMS. This distinct quality value will be dependent on some individual appreciations assigned by customers to basic services. We also discuss some improvements concerning the fuzzification parts of controllers.
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