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pro vyhledávání: '"Bezdek, James"'
Examining most streaming clustering algorithms leads to the understanding that they are actually incremental classification models. They model existing and newly discovered structures via summary information that we call footprints. Incoming data is
Externí odkaz:
http://arxiv.org/abs/2010.00635
The VAT method is a visual technique for determining the potential cluster structure and the possible number of clusters in numerical data. Its improved version, iVAT, uses a path-based distance transform to improve the effectiveness of VAT for "toug
Externí odkaz:
http://arxiv.org/abs/2008.09570
Autor:
Rathore, Punit, Kumar, Dheeraj, Rajasegarar, Sutharshan, Palaniswami, Marimuthu, Bezdek, James C.
Trajectory prediction (TP) is of great importance for a wide range of location-based applications in intelligent transport systems such as location-based advertising, route planning, traffic management, and early warning systems. In the last few year
Externí odkaz:
http://arxiv.org/abs/1806.03582
Cluster analysis is used to explore structure in unlabeled data sets in a wide range of applications. An important part of cluster analysis is validating the quality of computationally obtained clusters. A large number of different internal indices h
Externí odkaz:
http://arxiv.org/abs/1801.02937
Autor:
Nguyen, Tien Thanh, Nguyen, Thi Thu Thuy, Pham, Xuan Cuong, Liew, Alan Wee-Chung, Bezdek, James C.
In this study, we introduce an ensemble-based approach for online machine learning. The ensemble of base classifiers in our approach is obtained by learning Naive Bayes classifiers on different training sets which are generated by projecting the orig
Externí odkaz:
http://arxiv.org/abs/1704.07938
Autor:
Kowsar, Yousef, Moshtaghi, Masud, Velloso, Eduardo, Bezdek, James C., Kulik, Lars, Leckie, Christopher
Publikováno v:
In Information Sciences January 2022 582:198-214
It has been noticed that some external CVIs exhibit a preferential bias towards a larger or smaller number of clusters which is monotonic (directly or inversely) in the number of clusters in candidate partitions. This type of bias is caused by the fu
Externí odkaz:
http://arxiv.org/abs/1606.05596