viralx_knn_shap: Explain K Nearest Neighbor Model using SHAP values

In viralx: Explainers for Regression Models in HIV Research

Explain K Nearest Neighbor Model using SHAP values

Description

This function calculates SHAP (SHapley Additive exPlanations) values for a K-Nearest Neighbors (KNN) model trained on HIV data with specified hyperparameters.

Usage

viralx_knn_shap(
  vip_featured,
  hiv_data,
  knn_hyperparameters,
  vip_train,
  vip_new,
  orderings
)

Arguments

vip_featured	The name of the response variable to explain.
hiv_data	The training dataset containing predictor variables and the response variable.
knn_hyperparameters	A list of hyperparameters for the KNN model, including: neighbors: The number of neighbors to consider. weight_func: The weight function to use. dist_power: The distance power parameter.
vip_train	The dataset used for training the KNN model.
vip_new	The dataset for which SHAP values are calculated.
orderings	The number of orderings for SHAP value calculations.

Value

A list of SHAP values for each observation in vip_new.

Examples

## Not run: 
set.seed(123)
hiv_data <- train2
knn_hyperparameters <- list(neighbors = 5, weight_func = "optimal", dist_power = 0.3304783)
vip_featured <- "cd_2022"
vip_train <- hiv_data
vip_new <- vip_train[1, ]
orderings <- 20
viralx_knn_shap(vip_featured, hiv_data, knn_hyperparameters, vip_train, vip_new, orderings)

## End(Not run)

viralx documentation built on Aug. 8, 2025, 7:34 p.m.