ts_fc_evaluation_results: A data frame of 1000 time series data forecasting method...
In mowomoyela/tsfcmethodr: Classification methods to predict best performing forecasting method of a ts
Description
A data frame containing 1000 different univariate and
multivariate time series data from the tstaxonomyr R package. For each one
is given the best performing forecasting method out of the seven
possible ones: 'random walk', 'exponentiel smoothing', 'arima', 'svm',
'ann', 'xgboost' and 'cart'.
Usage
1
Format
A data frame with 1000 elements.
Each row represents a time series object with it's best performing
forecasting method. The following columns are provided:
- ts_name
The name of the time series from the tstaxonomyr package
- best_fc_method
The best performing forecasting method
mowomoyela/tsfcmethodr documentation built on May 15, 2019, 4:47 p.m.
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Description
A data frame containing 1000 different univariate and multivariate time series data from the tstaxonomyr R package. For each one is given the best performing forecasting method out of the seven possible ones: 'random walk', 'exponentiel smoothing', 'arima', 'svm', 'ann', 'xgboost' and 'cart'.
Usage
1 |
Format
A data frame with 1000 elements. Each row represents a time series object with it's best performing forecasting method. The following columns are provided:
- ts_name
The name of the time series from the tstaxonomyr package
- best_fc_method
The best performing forecasting method
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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