THA_features: Calculate features from Talagala, Hyndman, Athanaspoulos and...
In robjhyndman/M4metalearning: Metalearning Tools For Time Series Forecasting
Description
Usage
Arguments
Examples
View source: R/generate_classif_problem.R
Description
For each series in dataset, the feature set used in
(Talagala, Hyndman and Athanasopoulos, 2018) is calculated
and added to the forec_err_dataset. A tibble named features
is added.
Usage
1
THA_features(dataset, n.cores = 1)
Arguments
dataset
A list the elements having a ts object with the name x
n.cores
The number of cores to be used. n.cores > 1 means parallel processing.
Examples
1
2
processed <- generate_THA_features(Mcomp::M3[c(1:3)], n.cores=1)
processed[[1]]$features
robjhyndman/M4metalearning documentation built on May 21, 2019, 12:22 p.m.
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Description Usage Arguments Examples
View source: R/generate_classif_problem.R
Description
For each series in dataset, the feature set used in
(Talagala, Hyndman and Athanasopoulos, 2018) is calculated
and added to the forec_err_dataset. A tibble named features
is added.
Usage
1 | THA_features(dataset, n.cores = 1)
|
Arguments
dataset |
A list the elements having a |
n.cores |
The number of cores to be used. |
Examples
1 2 | processed <- generate_THA_features(Mcomp::M3[c(1:3)], n.cores=1)
processed[[1]]$features
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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