Description Usage Arguments Value
View source: R/deepregression.R
Compile a Deep Distributional Regression Model
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list_pred_param |
list of input-output(-lists) generated from
|
weights |
vector of positive values; optional (default = 1 for all observations) |
optimizer |
optimizer used. Per default Adam |
model_fun |
which function to use for model building (default |
monitor_metrics |
Further metrics to monitor |
from_preds_to_output |
function taking the list_pred_param outputs and transforms it into a single network output |
loss |
the model's loss function; per default evaluated based on
the arguments |
additional_penalty |
a penalty that is added to the negative log-likelihood; must be a function of model$trainable_weights with suitable subsetting |
... |
arguments passed to |
a list with input tensors and output tensors that can be passed
to, e.g., keras_model
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