waterfall_plot | R Documentation |
The waterfall_plot
function is a bar chart that displays the positive and
negative contributions across sequential data points, visualizing how each
variable's contributions change for a single observation.
waterfall_plot(
object,
obs_num = NULL,
title = NULL,
geo.unit = NULL,
geo.id = NULL,
obs_name = NULL
)
object |
Enter the name of the object that contains the model's contributions and results obtained using the Explain function. |
obs_num |
observation number (only one) |
title |
plot title |
geo.unit |
The name of the stratum variable in the BARP model as a character. |
geo.id |
Enter a single value of the stratum variable as a character. |
obs_name |
Enter the name of the vector containing observation IDs or names. |
The function returns a waterfall plot.
plot_out |
The waterfall plot of the observation at index |
## Friedman data
set.seed(2025)
n <- 200
p <- 5
X <- data.frame(matrix(runif(n * p), ncol = p))
y <- 10 * sin(pi* X[ ,1] * X[,2]) +20 * (X[,3] -.5)^2 + 10 * X[ ,4] + 5 * X[,5] + rnorm(n)
## Using dbarts
model <- dbarts::bart (X, y, keeptrees = TRUE, ndpost = 200)
# prediction wrapper function
pfun <- function (object, newdata) {
predict(object, newdata)
}
# Calculate shapley values
model_exp <- Explain(model, X = X, pred_wrapper=pfun)
# Waterfall plot of 100th observation
waterfall_plot(model_exp, obs_num=100)
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