Description Usage Arguments Value Examples
This is a function to generate a ann classification model for the
1000 time series from the tstaxonomyr R package. The best fitted ann model is
identified based on the k-fold cv_nfold
cross-validation and the
number of rounds n_round
. The method 'nnet' from 'caret' package is
fitted and afterwards returned. As input is only required the n_round
,
cv_nfold
and tune_length
with a number between 1 and 100. Also,
for ts_taxonomy
only 'v1' for the basic taxonomy or 'v2' for the
ligther feature selected taxonomy of the tstaxonomyr R package are allowed.
Otherwise the function returns an error message.
1 2 | train_ann(n_round = 10, cv_nfold = 10, tune_length = 10,
ts_taxonomy = "v1")
|
n_round |
Number of cross-validation rounds. |
cv_nfold |
Number of folds of cross-validation. |
tune_length |
Number of model tuning intervals. |
ts_taxonomy |
Either 'v1' or 'v2'. v1 uses the default time series taxonomy and v2 the feature selected ts taxonomy of the tstaxonomyr package. |
The best fitted ann classification model.
1 | fitted_model <- train_ann()
|
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