Comparison of different methods

@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.