Titlebook: Data Stream Mining & Processing; Third International Sergii Babichev,Dmytro Peleshko,Olena Vynokurova Conference proceedings 2020 Springer

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https://doi.org/10.1007/978-3-031-08443-0 clustering various types of datasets using density-based DBSCAN clustering algorithm implemented based on Inductive Methods of Objective Clustering (IMOC). Implementation of the IMOC technique assumes division of the initial dataset into two similar subsets contained the same number of pairwise sim

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https://doi.org/10.1007/978-3-031-08443-0’s risks of a virtual IT company. A detailed justification of each selected risk parameter that influences on the success of the investment project of the virtual IT Company has done. A developed algorithm for assessing the investment risk of the virtual IT company is based on machine learning and u

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Hiroshi Okamoto,Kazuhisa Ichikawathe key point descriptors space into the space of the data statistical distributions to increase the speed of data processing. These distributions are based on the set of component values obtained by partitioning descriptors into non-intersecting fragments. The compression of data into the fixed set

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