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@inbook{61501, author = {Vrbka, Jaromír}, address = {Cham, Švýcarsko}, booktitle = {Using artificial neural networks for timeseries smoothing and forecasting: case studies in economics}, edition = {1. vyd.}, editor = {Janusz Kacrpzyk}, keywords = {neural networks; decisions tree; Gaussian process; linear regression; random forest}, howpublished = {tištěná verze "print"}, language = {eng}, location = {Cham, Švýcarsko}, isbn = {978-3-030-75648-2}, pages = {137-186}, publisher = {Springer Nature Switzerland AG}, title = {Comparison of different methods}, url = {https://link.springer.com/book/10.1007%2F978-3-030-75649-9#authorsandaffiliationsbook}, year = {2021} }
TY - CHAP ID - 61501 AU - Vrbka, Jaromír PY - 2021 TI - Comparison of different methods VL - Studies in computational intelligence (979) PB - Springer Nature Switzerland AG CY - Cham, Švýcarsko SN - 9783030756482 KW - neural networks KW - decisions tree KW - Gaussian process KW - linear regression KW - random forest UR - https://link.springer.com/book/10.1007%2F978-3-030-75649-9#authorsandaffiliationsbook N2 - The author argues that predictors in this case are neural networks, the number of test examples is 1221 and the number of training examples is 2442. ER -
VRBKA, Jaromír. Comparison of different methods. In Janusz Kacrpzyk. \textit{Using artificial neural networks for timeseries smoothing and forecasting: case studies in economics}. 1. vyd. Cham, Švýcarsko: Springer Nature Switzerland AG, 2021, p.~137-186. Studies in computational intelligence (979). ISBN~978-3-030-75648-2.
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