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pro vyhledávání: '"Nagaraj Honnikoll"'
Autor:
Ishwar Baidari, Nagaraj Honnikoll
Publikováno v:
The Computer Journal. 66:1-15
Boosting is a generally known technique to convert a group of weak learners into a powerful ensemble. To reach this desired objective successfully, the modules are trained with distinct data samples and the hypotheses are combined in order to achieve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1755745687c22c7c5fbf8313aec83fb2
https://doi.org/10.1093/comjnl/bxab138
https://doi.org/10.1093/comjnl/bxab138
Autor:
Nagaraj Honnikoll, Ishwar Baidari
Publikováno v:
Expert Systems with Applications. 183:115303
The majority of online learners assume that the data distribution to be learned is established in advance. There are many real-world problems where the distribution of the data changes as a function of time. Variations in data streams data distributi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::294f33a73a08585fa132038364c9505f
https://doi.org/10.1016/j.eswa.2021.115303
https://doi.org/10.1016/j.eswa.2021.115303
Autor:
Nagaraj Honnikoll, Ishwar Baidari
Publikováno v:
Expert Systems with Applications. 160:113723
Target distributional change occurring in a data stream known as concept drift, causes a challenging task for an online learning method, as the accuracy of an online learning method may decrease due to these changes. In this paper, the Accuracy Weigh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::de80237c13e0edc1fe8498bcf09909ff
https://doi.org/10.1016/j.eswa.2020.113723
https://doi.org/10.1016/j.eswa.2020.113723