nn_domain_score {viraldomain}R Documentation

Calculate the Neural Network model domain applicability score

Description

This function fits a Neural Network model to the provided data and computes a domain applicability score based on PCA distances.

Usage

nn_domain_score(
  featured_col,
  train_data,
  nn_hyperparameters,
  test_data,
  threshold_value
)

Arguments

featured_col

The name of the featured column in the training data.

train_data

The training data used to fit the Neural Network model.

nn_hyperparameters

A list of Neural Network hyperparameters, including hidden_units, penalty, and epochs.

test_data

The testing domain data used to calculate the domain applicability score.

threshold_value

The threshold value for domain applicability scoring.

Value

A tibble with the domain applicability scores.

Examples

set.seed(123)
library(dplyr)
featured_col <- "cd_2022"
# Specifying features for training and testing procedures
train_data = viral %>%
  dplyr::select(cd_2022, vl_2022)
test_data = sero 
nn_hyperparameters <- list(hidden_units = 1, penalty = 0.3746312,  epochs =  480)
threshold_value <- 0.99
nn_domain_score(featured_col, train_data, nn_hyperparameters, test_data, threshold_value)

[Package viraldomain version 0.0.7 Index]