build_dnn {survdnn} | R Documentation |
Build a Deep Neural Network for Survival Analysis
Description
Constructs a multilayer perceptron (MLP) with batch normalization, activation functions, and dropout. Used internally by [survdnn()] to define the model architecture.
Usage
build_dnn(input_dim, hidden, activation = "relu", output_dim = 1L)
Arguments
input_dim |
Integer. Number of input features. |
Integer vector. Sizes of the hidden layers (e.g., c(32, 16)). | |
activation |
Character. Name of the activation function to use in each layer. Supported options: '"relu"', '"leaky_relu"', '"tanh"', '"sigmoid"', '"gelu"', '"elu"', '"softplus"'. |
output_dim |
Integer. Output layer dimension (default = 1). |
Value
A 'nn_sequential' object representing the network.
Examples
net <- build_dnn(10, hidden = c(64, 32), activation = "relu")
[Package survdnn version 0.6.0 Index]