TY - JOUR
T1 - Some properties of the classification algorithms using ensemble kernels
AU - Odinokikh, N.
AU - Berikov, V.
N1 - Funding Information:
The work was partly supported by RFBR grants 18-07-00600 and 19-29-01175. The study was carried out within the framework of the state contract of Sobolev Institute of Mathematics (project no 0314-2019-0015).
Publisher Copyright:
© 2021 Institute of Physics Publishing. All rights reserved.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/1/4
Y1 - 2021/1/4
N2 - In this paper, we study the properties of the KCCE algorithm (Kernel-based Classification with Cluster Ensemble) proposed in our previous publication. Different strategies for choosing the ensemble weights are investigated from the point of view of their influence on the quality and speed of the algorithm. We perform numerical experiments with the algorithm on real datasets from the UCI repository under conditions of artificially added noise at different levels.
AB - In this paper, we study the properties of the KCCE algorithm (Kernel-based Classification with Cluster Ensemble) proposed in our previous publication. Different strategies for choosing the ensemble weights are investigated from the point of view of their influence on the quality and speed of the algorithm. We perform numerical experiments with the algorithm on real datasets from the UCI repository under conditions of artificially added noise at different levels.
UR - http://www.scopus.com/inward/record.url?scp=85100711322&partnerID=8YFLogxK
U2 - 10.1088/1742-6596/1715/1/012011
DO - 10.1088/1742-6596/1715/1/012011
M3 - Conference article
AN - SCOPUS:85100711322
VL - 1715
JO - Journal of Physics: Conference Series
JF - Journal of Physics: Conference Series
SN - 1742-6588
IS - 1
M1 - 012011
T2 - International Conference on Marchuk Scientific Readings 2020, MSR 2020
Y2 - 19 October 2020 through 23 October 2020
ER -