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Tuncel, Kerem Sinan, Baydogan, Mustafa Gokce (2018) Autoregressive forests for multivariate time series modeling. Pattern Recognition, 73. 202-215 doi:10.1016/j.patcog.2017.08.016

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Reference TypeJournal (article/letter/editorial)
TitleAutoregressive forests for multivariate time series modeling
JournalPattern Recognition
AuthorsTuncel, Kerem SinanAuthor
Baydogan, Mustafa GokceAuthor
Year2018 (January)Volume73
PublisherElsevier BV
DOIdoi:10.1016/j.patcog.2017.08.016Search in ResearchGate
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Mindat Ref. ID9367139Long-form Identifiermindat:1:5:9367139:0
GUID0
Full ReferenceTuncel, Kerem Sinan, Baydogan, Mustafa Gokce (2018) Autoregressive forests for multivariate time series modeling. Pattern Recognition, 73. 202-215 doi:10.1016/j.patcog.2017.08.016
Plain TextTuncel, Kerem Sinan, Baydogan, Mustafa Gokce (2018) Autoregressive forests for multivariate time series modeling. Pattern Recognition, 73. 202-215 doi:10.1016/j.patcog.2017.08.016
In(2018) Pattern Recognition Vol. 73. Elsevier BV

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Baydogan, Mustafa Gokce, Runger, George (2015) Learning a symbolic representation for multivariate time series classification. Data Mining and Knowledge Discovery, 29. 400-422 doi:10.1007/s10618-014-0349-y
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Orsenigo, C., Vercellis, C. (2010) Combining discrete SVM and fixed cardinality warping distances for multivariate time series classification. Pattern Recognition, 43 (11). 3787-3794 doi:10.1016/j.patcog.2010.06.005
Li, Qingzhe, Zhao, Liang, Lee, Yi-Ching, Sassan, Avesta, Lin, Jessica (2021) CPM: A general feature dependency pattern mining framework for contrast multivariate time series. Pattern Recognition, 112. 107711pp. doi:10.1016/j.patcog.2020.107711
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