Classification of stochastic processes with topological data analysis

İsmail Güzel*, Atabey Kaygun

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1 Atıf (Scopus)

Özet

In this study, we demonstrate that engineered topological features can distinguish time series sampled from different stochastic processes with different noise characteristics, in both balanced and unbalanced sampling schemes. We compare our classification results against the results of the same classification on features coming from descriptive statistics and the wavelet transform. We conclude that machine learning models built on engineered topological features alone perform consistently better than those built on the standard statistical and wavelet features for time series classification tasks. We also apply dimension reduction techniques to our engineered features and compare the result of our classification models before and after dimensionality reduction. Finally, we also show that in our calculations of the engineered topological features, employing parallel computing methods does yield significant improvements in run time and memory footprint.

Orijinal dilİngilizce
Makale numarasıe7732
DergiConcurrency Computation Practice and Experience
Hacim35
Basın numarası24
DOI'lar
Yayın durumuYayınlandı - 1 Kas 2023

Bibliyografik not

Publisher Copyright:
© 2023 John Wiley & Sons, Ltd.

Finansman

Computing resources used in this work were provided by the National Center for High-Performance Computing of Türkiye (UHeM) under the first author's project which Grants number 4010242021. We also thank the two anonymous reviewers whose comments helped to improve the quality of this study. Computing resources used in this work were provided by the National Center for High‐Performance Computing of Türkiye (UHeM) under the first author's project which Grants number 4010242021. We also thank the two anonymous reviewers whose comments helped to improve the quality of this study.

FinansörlerFinansör numarası
National Center for High-Performance Computing of Türkiye
National Center for High‐Performance Computing of Türkiye
Ulusal Yüksek Başarımlı Hesaplama Merkezi, Istanbul Teknik Üniversitesi4010242021

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