Classification of Multifractal Time Series by Decision Tree Methods

Булах, В. А.; Кіріченко, Л. О.; Радівілова, Т. А.

Публікація:
Classification of Multifractal Time Series by Decision Tree Methods

dc.contributor.author	Булах, В. А.
dc.contributor.author	Кіріченко, Л. О.
dc.contributor.author	Радівілова, Т. А.
dc.date.accessioned	2018-06-05T18:55:35Z
dc.date.available	2018-06-05T18:55:35Z
dc.date.issued	2018
dc.description.abstract	The article considers classification task of model fractal time series by the methods of machine learning. To classify the series, it is proposed to use the meta algorithms based on decision trees. To modeling the fractal time series, binomial stochastic cascade processes are used. Classification of time series by the ensembles of decision trees models is carried out. The analysis indicates that the best results are obtained by the methods of bagging and random forest which use regression trees.	uk_UA
dc.identifier.citation	Bulakh V. Classification of Multifractal Time Series by Decision Tree Methods / V. Bulakh, L. Kirichenko, T. Radivilova // Proceedings of the 14th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer, May 14-17, 2018. – V. I. – Kyiv. – Р. 457–460.	uk_UA
dc.identifier.uri	http://openarchive.nure.ua/handle/document/5840
dc.language.iso	en	uk_UA
dc.publisher	КНУ	uk_UA
dc.subject	multifractal time series	uk_UA
dc.subject	binomial stochastic cascade	uk_UA
dc.subject	classification of time series	uk_UA
dc.subject	Random Forest	uk_UA
dc.subject	Bagging	uk_UA
dc.title	Classification of Multifractal Time Series by Decision Tree Methods	uk_UA
dc.type	Thesis	uk_UA
dspace.entity.type	Publication