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Wyszukujesz frazę "disjoint clusters" wg kryterium: Temat


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Tytuł:
All splitting logics in the lattice NEXT(KTB:30A)
Autorzy:
Kostrzycka, Z.
Powiązania:
https://bibliotekanauki.pl/articles/121995.pdf
Data publikacji:
2016
Wydawca:
Uniwersytet Humanistyczno-Przyrodniczy im. Jana Długosza w Częstochowie. Wydawnictwo Uczelniane
Tematy:
logika modalna
ramka Kripkego
klastry rozłączne
modal logic
Kripke’s frome
disjoint clusters
Opis:
We examine a special modal logic which is a normal extension of the Brouwer modal logic. It is determined by linearly ordered chains of clusters and the relation between clusters is reflexive and symmetric. The appropriate axiomatization of this logic is proposed in the papers [11] and [12]. There is also proved that all normal extensions of the investigated logic are Kripke complete and have f.m.p. Unfortunately, the cardinality of this family is continuum [13]. One may imagine that the structure of the lattice of these extensions is immensely complex. Then we use the technics of splitting to characterize this lattice and to describe some quite simple fragments. We characterize all the logics that split the lattice.
Źródło:
Scientific Issues of Jan Długosz University in Częstochowa. Mathematics; 2016, 21; 31-61
2450-9302
Pojawia się w:
Scientific Issues of Jan Długosz University in Częstochowa. Mathematics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A density-based method for the identification of disjoint and non-disjoint clusters with arbitrary and non-spherical shapes
Autorzy:
Ben Ncir, Chiheb-Eddine
Powiązania:
https://bibliotekanauki.pl/articles/2097971.pdf
Data publikacji:
2021
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
overlapping clustering
non-disjoint clusters
density-based methods
clusters with non-spherical shapes
Opis:
The ability of clustering methods to build both disjoint and non-disjoint partitionings of data has become an important issue in unsupervised learning. Although this problem has been studied during the last decades resulting in several proposed overlapping clustering methods in the literature, most of existing methods fail to look for clusters having arbitrary and non-spherical shapes. In addition, most of these existing methods require to pre-configure the number of clusters in prior, which is not a trivial task in real life application of clustering. To solve all these issues, we propose in this work a new density based overlapping clustering method, referred to as OC-DD, which is able to detect both disjoint and non-disjoint partitioning even when boundaries between clusters have complex separations with arbitrary forms and shapes. The proposed method is based on density and distances to detect highly dense regions and connected groups in data without the necessity to pre-configure the number of clusters. Experiments performed on artificial and real multi-labeled datasets have shown the effectiveness of the proposed method compared to the existing ones.
Źródło:
Computer Science; 2021, 22 (2); 169-190
1508-2806
2300-7036
Pojawia się w:
Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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