nnetar_params {modeltime} | R Documentation |
Tuning Parameters for NNETAR Models
Description
Tuning Parameters for NNETAR Models
Usage
num_networks(range = c(1L, 100L), trans = NULL)
Arguments
range |
A two-element vector holding the defaults for the smallest and largest possible values, respectively. If a transformation is specified, these values should be in the transformed units. |
trans |
A |
Details
The main parameters for NNETAR models are:
-
non_seasonal_ar
: Number of non-seasonal auto-regressive (AR) lags. Often denoted "p" in pdq-notation. -
seasonal_ar
: Number of seasonal auto-regressive (SAR) lags. Often denoted "P" in PDQ-notation. -
hidden_units
: An integer for the number of units in the hidden model. -
num_networks
: Number of networks to fit with different random starting weights. These are then averaged when producing forecasts. -
penalty
: A non-negative numeric value for the amount of weight decay. -
epochs
: An integer for the number of training iterations.
See Also
non_seasonal_ar()
, seasonal_ar()
, dials::hidden_units()
, dials::penalty()
, dials::epochs()
Examples
num_networks()