Titlebook: Rough Sets; International Joint Sheela Ramanna,Chris Cornelis,Davide Ciucci Conference proceedings 2021 Springer Nature Switzerland AG 202

Cytokines

Classification of Multi-class Imbalanced Data: Data Difficulty Factors and Selected Methods for Imprbeen sufficiently studied so far. Therefore, in this paper we summarize the few literature works on the difficulty factors and present our own latest research results. The binary method for an identification of the types of minority examples is generalized for multiple imbalance classes. The second

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Attribute Reduction Using Functional Dependency Relations in Rough Set Theorybetween functional dependency relations, attribute reduction, and closure operators. We use the partial order for dependencies to show that reducts of an information system can be obtained from the maximal elements of a functional dependency relation.

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receptors

Many-Valued Dynamic Object-Oriented Inheritance and Approximationsand objects are first-class citizens. In the current paper we provide a novel formal framework for many-valued object-oriented inheritance in rule-based query languages. We also relate the framework to rough set-like approximate reasoning. Rough sets and their generalizations have intensively been s

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Possibility Distributions Generated by Intuitionistic ,-Fuzzy Sets to intuitionistic .-fuzzy sets based on a complete residuated lattice with an involution. Moreover, taking the .ukasiewicz .-chains as structures of truth degrees, we propose an algorithm to compute the intuitionistic .-fuzzy set corresponding to a given possibility distribution, in case it exists.

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