| Name : R-WaveletGBM
| |
| Version : 0.1.0
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp156.5.1
| Date : 2024-07-04 14:10:00
|
| Group : Development/Libraries/Other
| Source RPM : R-WaveletGBM-0.1.0-lp156.5.1.src.rpm
|
| Size : 0.02 MB
| |
| Packager : https://www_suse_com/
| |
| Summary : Wavelet Based Gradient Boosting Method
|
Description :
Wavelet decomposition method is very useful for modelling noisy time
series data. Wavelet decomposition using \'haar\' algorithm has been
implemented to developed hybrid Wavelet GBM (Gradient Boosting Method)
model for time series forecasting using algorithm by Anjoy and Paul
(2017) < DOI:10.1007/s00521-017-3289-9>.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/15.6/x86_64 |
