from_preds_to_dist {deepregression} R Documentation

## Define Predictor of a Deep Distributional Regression Model

### Description

Define Predictor of a Deep Distributional Regression Model

### Usage

from_preds_to_dist(
list_pred_param,
family = NULL,
output_dim = 1L,
mapping = NULL,
from_family_to_distfun = make_tfd_dist,
from_distfun_to_dist = distfun_to_dist,
add_layer_shared_pred = function(x, units) layer_dense(x, units = units, use_bias =
FALSE),
trafo_list = NULL
)


### Arguments

 list_pred_param list of input-output(-lists) generated from subnetwork_init family see ?deepregression; if NULL, concatenated list_pred_param entries are returned (after applying mapping if provided) output_dim dimension of the output mapping a list of integers. The i-th list item defines which element elements of list_pred_param are used for the i-th parameter. For example, mapping = list(1,2,1:2) means that list_pred_param[[1]] is used for the first distribution parameter, list_pred_param[[2]] for the second distribution parameter and list_pred_param[[3]] for both distribution parameters (and then added once to list_pred_param[[1]] and once to list_pred_param[[2]]) from_family_to_distfun function to create a dist_fun (see ?distfun_to_dist) from the given character family from_distfun_to_dist function creating a tfp distribution based on the prediction tensors and dist_fun. See ?distfun_to_dist add_layer_shared_pred layer to extend shared layers defined in mapping trafo_list a list of transformation function to convert the scale of the additive predictors to the respective distribution parameter

### Value

a list with input tensors and output tensors that can be passed to, e.g., keras_model

[Package deepregression version 1.0.0 Index]