| Name : R-tsensembler
| |
| Version : 0.1.0
| Vendor : obs://build_opensuse_org/devel:languages:R
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| Release : lp153.15.3
| Date : 2024-06-14 12:13:08
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| Group : Development/Libraries/Other
| Source RPM : R-tsensembler-0.1.0-lp153.15.3.src.rpm
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| Size : 0.59 MB
| |
| Packager : (none)
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| Summary : Dynamic Ensembles for Time Series Forecasting
|
Description :
A framework for dynamically combining forecasting models for time
series forecasting predictive tasks. It leverages machine learning
models from other packages to automatically combine expert advice using
metalearning and other state-of-the-art forecasting combination
approaches. The predictive methods receive a data matrix as input,
representing an embedded time series, and return a predictive ensemble
model. The ensemble use generic functions \'predict()\' and \'forecast()\'
to forecast future values of the time series. Moreover, an ensemble can
be updated using methods, such as \'update_weights()\' or
\'update_base_models()\'. A complete description of the methods can be
found in: Cerqueira, V., Torgo, L., Pinto, F., and Soares, C.
\"Arbitrated Ensemble for Time Series Forecasting.\" to appear at: Joint
European Conference on Machine Learning and Knowledge Discovery in
Databases. Springer International Publishing, 2017; and Cerqueira, V.,
Torgo, L., and Soares, C.: \"Arbitrated Ensemble for Solar Radiation
Forecasting.\" International Work-Conference on Artificial Neural
Networks. Springer, 2017 < doi:10.1007/978-3-319-59153-7_62>.
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RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
