safely_detect_interactions {rSAFE} | R Documentation |
Detecting Interactions via Permutation Approach
Description
The safely_detect_interactions() function detects second-order interactions based on predictions made by a surrogate model. For each pair of features it performs values permutation in order to evaluate their non_additive effect.
Usage
safely_detect_interactions(
explainer,
inter_param = 0.5,
inter_threshold = 0.5,
verbose = TRUE
)
Arguments
explainer |
DALEX explainer created with explain() function |
inter_param |
numeric, a positive value indicating which of single observation non-additive effects are to be regarded as significant, the higher value the higher non-additive effect has to be to be taken into account |
inter_threshold |
numeric, a value from |
verbose |
logical, if progress bar is to be printed |
Value
dataframe object containing interactions effects greater than or equal to the specified inter_threshold
See Also
Examples
library(DALEX)
library(randomForest)
library(rSAFE)
data <- apartments[1:500,]
set.seed(111)
model_rf <- randomForest(m2.price ~ construction.year + surface + floor +
no.rooms + district, data = data)
explainer_rf <- explain(model_rf, data = data[,2:6], y = data[,1])
safely_detect_interactions(explainer_rf, inter_param = 0.25,
inter_threshold = 0.2, verbose = TRUE)