Time series classification based on fractal properties

Abstract

The article considers classification task of fractal time series by the meta algorithms based on decision trees. Binomial multiplicative stochastic cascades are used as input time series. Comparative analysis of the classification approaches based on different features is carried out. The results indicate the advantage of the machine learning methods over the traditional estimating the degree of self-similarity.

4 pages, 2 figures, 3 equations, 1 table

References in corpus (2)

• Forecasting Weakly Correlated Time Series in Tasks of Electronic Commerce
• Investigation of Multifractal Properties of Additive Data Stream

Cited by in corpus (1)

• The Methods to Improve Quality of Service by Accounting Secure Parameters