Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Artur Starczewski"'
Publikováno v:
Journal of Artificial Intelligence and Soft Computing Research. 11:319-330
Data clustering is an important method used to discover naturally occurring structures in datasets. One of the most popular approaches is the grid-based concept of clustering algorithms. This kind of method is characterized by a fast processing time
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8a351cd60b26e5253ce7c57956eb1171
https://doi.org/10.2478/jaiscr-2021-0019
https://doi.org/10.2478/jaiscr-2021-0019
Publikováno v:
Journal of Artificial Intelligence and Soft Computing Research. 10:209-221
Clustering is an attractive technique used in many fields in order to deal with large scale data. Many clustering algorithms have been proposed so far. The most popular algorithms include density-based approaches. These kinds of algorithms can identi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e92a2c93311cb09d02d826b8f4bbf1a2
https://doi.org/10.2478/jaiscr-2020-0014
https://doi.org/10.2478/jaiscr-2020-0014
Autor:
Artur Starczewski
Publikováno v:
Artificial Intelligence and Soft Computing ISBN: 9783030879853
ICAISC (1)
ICAISC (1)
Data clustering is one of the most important methods used to discover naturally occurring structures in datasets. One of the most popular clustering algorithms is the Density-Based Spatial Clustering of Applications with Noise (DBSCAN). This algorith
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4085cf01b9c6cc8c5f23ad88f894fa5a
https://doi.org/10.1007/978-3-030-87986-0_32
https://doi.org/10.1007/978-3-030-87986-0_32
Autor:
Andrzej Cader, Artur Starczewski
Publikováno v:
Artificial Intelligence and Soft Computing ISBN: 9783030614003
ICAISC (1)
ICAISC (1)
Clustering is a very important technique used in many fields in order to deal with large datasets. In clustering algorithms, one of the most popular approaches is based on an analysis of clusters density. Density-based algorithms include different me
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5e6e94a29f4974e6e9d60774666e71d4
https://doi.org/10.1007/978-3-030-61401-0_52
https://doi.org/10.1007/978-3-030-61401-0_52
Autor:
Andrzej Cader, Artur Starczewski
Publikováno v:
Artificial Intelligence and Soft Computing ISBN: 9783030209148
ICAISC (2)
ICAISC (2)
Clustering is an attractive technique used in many fields and lots of clustering algorithms have been proposed so far. The Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is one of the most popular algorithms, which has been wide
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::84660b0656b361dc5bed97d2a323beb0
https://doi.org/10.1007/978-3-030-20915-5_38
https://doi.org/10.1007/978-3-030-20915-5_38
Autor:
Artur Starczewski
Publikováno v:
Pattern Analysis and Applications. 20:687-700
In this paper, a new cluster validity index which can be considered as a measure of the accuracy of the partitioning of data sets is proposed. The new index, called the STR index, is defined as the product of two components which determine changes of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ce15bd7db8b74dcddd87f41fd3d08cde
https://doi.org/10.1007/s10044-015-0525-8
https://doi.org/10.1007/s10044-015-0525-8
Publikováno v:
Artificial Intelligence and Soft Computing ISBN: 9783319912615
ICAISC (2)
ICAISC (2)
The fundamental issue of data clustering is an evaluation of results of clustering algorithms. Lots of methods have been proposed for cluster validation. The most popular approach is based on internal cluster validity indices. Among this kind of indi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::901557b9d35b9a90b3eed5b4e98f6c95
https://doi.org/10.1007/978-3-319-91262-2_39
https://doi.org/10.1007/978-3-319-91262-2_39
Autor:
Artur Starczewski, Adam Krzyżak
Publikováno v:
Artificial Intelligence and Soft Computing ISBN: 9783319590592
ICAISC (2)
ICAISC (2)
In this paper a detail analysis of an improvement of the Silhouette validity index is presented. This proposed approach is based on using an additional component which improves clusters validity assessment and provides better results during a cluster
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4a2dab5625ee3fdf597e17d16b3280ff
https://doi.org/10.1007/978-3-319-59060-8_16
https://doi.org/10.1007/978-3-319-59060-8_16
Autor:
Adam Krzyżak, Artur Starczewski
Publikováno v:
Artificial Intelligence and Soft Computing ISBN: 9783319590592
ICAISC (2)
ICAISC (2)
In this paper a study of several cluster validity indices for real-life data sets is presented. Moreover, a new version of validity index is also proposed. All these indices can be considered as a measure of data partitioning accuracy and the perform
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::58cd0576b40a5050098f09c80cf68a45
https://doi.org/10.1007/978-3-319-59060-8_15
https://doi.org/10.1007/978-3-319-59060-8_15
Autor:
Adam Krzyżak, Artur Starczewski
Publikováno v:
Artificial Intelligence and Soft Computing ISBN: 9783319393834
ICAISC (2)
ICAISC (2)
In this paper a modification of the well-known Silhouette validity index is proposed. This index, which can be considered a measure of the data set partitioning accuracy, enjoys significant popularity and is often used by researchers. The proposed mo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b5caacd1a09354a731fa0dd243af59d2
https://doi.org/10.1007/978-3-319-39384-1_10
https://doi.org/10.1007/978-3-319-39384-1_10