R/model.R
, R/model_ar.R
, R/model_arima.R
, and 6 more
get_model_specs.Rd
This function is used to extract the feature information from the model to be checked against the
corresponding feature information in the data passed to [explain()]
.
NOTE: You should never need to call this function explicitly. It is exported just to be easier accessible for users, see details.
get_model_specs(x)
# S3 method for default
get_model_specs(x)
# S3 method for ar
get_model_specs(x)
# S3 method for Arima
get_model_specs(x)
# S3 method for forecast_ARIMA
get_model_specs(x)
# S3 method for glm
get_model_specs(x)
# S3 method for lm
get_model_specs(x)
# S3 method for gam
get_model_specs(x)
# S3 method for ranger
get_model_specs(x)
# S3 method for workflow
get_model_specs(x)
# S3 method for xgb.Booster
get_model_specs(x)
Model object for the model to be explained.
A list with the following elements:
character vector with the feature names to compute Shapley values for
a named character vector with the labels as names and the class type as elements
a named list with the labels as names and character vectors with the factor levels as elements (NULL if the feature is not a factor)
If you are explaining a model not supported natively, you may (optionally) enable such checking by
creating this function yourself and passing it on to [explain()]
.
For model classes not supported natively, you NEED to create an analogue to [predict_model()]
. See it's
help file for details.
# Load example data
data("airquality")
airquality <- airquality[complete.cases(airquality), ]
# Split data into test- and training data
x_train <- head(airquality, -3)
x_explain <- tail(airquality, 3)
# Fit a linear model
model <- lm(Ozone ~ Solar.R + Wind + Temp + Month, data = x_train)
get_model_specs(model)
#> $labels
#> [1] "Solar.R" "Wind" "Temp" "Month"
#>
#> $classes
#> Solar.R Wind Temp Month
#> "numeric" "numeric" "numeric" "numeric"
#>
#> $factor_levels
#> $factor_levels$Solar.R
#> NULL
#>
#> $factor_levels$Wind
#> NULL
#>
#> $factor_levels$Temp
#> NULL
#>
#> $factor_levels$Month
#> NULL
#>
#>