CASI 2023
Check out my poster for CASI 2023.

You can find the GitHub repository for the poster here.
Installation
You can install the development version of interpretnn from GitHub with:
# install.packages("devtools")
devtools::install_github("andrew-mcinerney/interpretnn")
interpretnn()
The primary function in this package is interpretnn()
. It creates a more statistically-based object of an existing neural network object. Currently supports neural networks from nnet
, neuralnet
, keras
, ANN
, and torch
.
library(interpretnn)
intnn <- interpretnn(object)
A useful summary table can be generated using
summary(intnn)
and covariate-effect plots can be created using
plot(intnn, conf_int = TRUE)
More information about these functions and their arguments can be found in the documentation.