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seer  

Feature-Based Forecast Model Selection
View on CRAN: Click here


Download and install seer package within the R console
Install from CRAN:
install.packages("seer")

Install from Github:
library("remotes")
install_github("cran/seer")

Install by package version:
library("remotes")
install_version("seer", "1.1.8")



Attach the package and use:
library("seer")
Maintained by
Thiyanga Talagala
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-02-21
Latest Update: 2022-10-01
Description:
A novel meta-learning framework for forecast model selection using time series features. Many applications require a large number of time series to be forecast. Providing better forecasts for these time series is important in decision and policy making. We propose a classification framework which selects forecast models based on features calculated from the time series. We call this framework FFORMS (Feature-based FORecast Model Selection). FFORMS builds a mapping that relates the features of time series to the best forecast model using a random forest. 'seer' package is the implementation of the FFORMS algorithm. For more details see our paper at .
How to cite:
Thiyanga Talagala (2020). seer: Feature-Based Forecast Model Selection. R package version 1.1.8, https://cran.r-project.org/web/packages/seer. Accessed 18 Feb. 2025.
Previous versions and publish date:
1.1.4 (2020-02-21 18:20), 1.1.5 (2020-06-08 07:00), 1.1.6 (2021-06-01 06:50), 1.1.7 (2021-12-08 06:20)
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