Machine Learning in Classification Time Series with Fractal Properties
Електронного архіву Харківського національного університету радіоелектроніки (Open Access Repository of KHNURE)
Переглянути архів Інформація| Поле | Співвідношення | |
| Title |
Machine Learning in Classification Time Series with Fractal Properties
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| Creator |
Кіріченко, Л. О.
Булах, В. А. Радівілова, Т. А. |
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| Subject |
fractal time series
binomial stochastic cascade classification of time series Hurst exponent random forest detecting distributed denial-of-service attacks |
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| Description |
The article presents a novel method of fractal time series classification by meta-algorithms based on decision trees. The classification objects are fractal time series. For modeling, binomial stochastic cascade processes are chosen. Each class that was singled out unites model time series with the same fractal properties. Numerical experiments demonstrate that the best results are obtained by the random forest method with regression trees. A comparative analysis of the classification approaches, based on the random forest method, and traditional estimation of self-similarity degree are performed. The results show the advantage of machine learning methods over traditional time series evaluation. The results were used for detecting denial-of-service (DDoS) attacks and demonstrated a high probability of detection. |
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| Date |
2019-06-19T08:43:01Z
2019-06-19T08:43:01Z 2019 |
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| Type |
Article
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| Identifier |
Kirichenko L. Machine Learning in Classification Time Series with Fractal Properties / L. Kirichenko, V. Bulakh, T. Radivilova // Data. – 2019. – vol.4(1) 5. – P. 1–13.
http://openarchive.nure.ua/handle/document/9453 |
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| Language |
en
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