safe_extraction {rSAFE}

Creating SAFE Extractor - an Object Used for Surrogate-Assisted Feature Extraction

Description

The safe_extraction() function creates a SAFE-extractor object which may be used later for surrogate feature extraction.

Usage

safe_extraction(
  explainer,
  response_type = "ale",
  grid_points = 50,
  N = 200,
  penalty = "MBIC",
  nquantiles = 10,
  no_segments = 2,
  method = "complete",
  B = 500,
  collapse = "_",
  interactions = FALSE,
  inter_param = 0.25,
  inter_threshold = 0.25,
  verbose = TRUE
)

Arguments

explainer

DALEX explainer created with explain() function

response_type

character, type of response to be calculated, one of: "pdp", "ale". If features are uncorrelated, one can use "pdp" type - otherwise "ale" is strongly recommended.

grid_points

number of points on x-axis used for creating the PD/ALE plot, default 50

N

number of observations from the dataset used for creating the PD/ALE plot, default 200

penalty

penalty for introducing another changepoint, one of "AIC", "BIC", "SIC", "MBIC", "Hannan-Quinn" or numeric non-negative value

nquantiles

the number of quantiles used in integral approximation

no_segments

numeric, a number of segments variable is to be divided into in case of founding no breakpoints

method

the agglomeration method to be used in hierarchical clustering, one of: "ward.D", "ward.D2", "single", "complete", "average", "mcquitty", "median", "centroid"

B

number of reference datasets used to calculate gap statistics

collapse

a character string to separate original levels while combining them to the new one

interactions

logical, if interactions between variables are to be taken into account

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 ⁠[0,1]⁠ interval indicating which interactions should be returned as significant. It corresponds to the percentage of observations for which interaction measure is greater than inter_param - if this percentage is less than inter_threshold then interaction effect is ignored.

verbose

logical, if progress bar is to be printed

Value

safe_extractor object containing information about variables transformation

See Also

safely_transform_categorical, safely_transform_continuous, safely_detect_interactions, safely_transform_data

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], verbose = FALSE)
safe_extractor <- safe_extraction(explainer_rf, grid_points = 30, N = 100, verbose = FALSE)
print(safe_extractor)
plot(safe_extractor, variable = "construction.year")