create_arena: Creates arena object
In arenar: Arena for the Exploration and Comparison of any ML Models

Description Usage Arguments Value Examples

Creates object with class arena_live or arena_static depending on the first argument. This method is always first in arenar workflow and you should specify all plots' parameters there.

create_arena(
  live = FALSE,
  N = 500,
  fi_N = NULL,
  fi_B = 10,
  grid_points = 101,
  shap_B = 10,
  funnel_nbins = 5,
  funnel_cutoff = 0.01,
  funnel_factor_threshold = 7,
  fairness_cutoffs = seq(0.05, 0.95, 0.05),
  max_points_number = 150,
  distribution_bins = seq(5, 40, 5),
  enable_attributes = TRUE,
  enable_custom_params = TRUE,
  cl = NULL
)

`live`	Defines if arena should start live server or generate static json
`N`	number of observations used to calculate dependence profiles
`fi_N`	number of observations used in feature importance
`fi_B`	Number of permutation rounds to perform each variable in feature importance
`grid_points`	number of points for profile
`shap_B`	Numer of random paths in SHAP
`funnel_nbins`	Number of partitions for numeric columns for funnel plot
`funnel_cutoff`	Threshold for categorical data. Entries less frequent than specified value will be merged into one category in funnel plot.
`funnel_factor_threshold`	Numeric columns with lower number of unique values than value of this parameter will be treated as factors in funnel plot.
`fairness_cutoffs`	vector of available cutoff levels for fairness panel
`max_points_number`	maximum size of sample to plot scatter plots in variable against another panel
`distribution_bins`	vector of available bins count for histogram
`enable_attributes`	Switch for generating attributes of observations and variables. It is required for custom params. Attributes can increase size of static Arena.
`enable_custom_params`	Switch to allowing user to modify observations and generate plots for them.
`cl`	Cluster used to run parallel computations (Do not work in live Arena)

Empty arena_static or arena_live class object.
arena_static:

explainer List of used explainers
observations_batches List of data frames added as observations
params Plots' parameters
plots_data List of generated data for plots

arena_live:

explainer List of used explainers
observations_batches List of data frames added as observations
params Plots' parameters
timestamp Timestamp of last modification

library("DALEX")
library("arenar")
library("dplyr", quietly=TRUE, warn.conflicts = FALSE)
# create a model
model <- glm(m2.price ~ ., data=apartments)
# create a DALEX explainer
explainer <- DALEX::explain(model, data=apartments, y=apartments$m2.price)
# prepare observations to be explained
observations <- apartments[1:3, ]
# rownames are used as labels for each observation
rownames(observations) <- paste0(observations$construction.year, "-", observations$surface, "m2")
# generate static arena for one model and 3 observations
arena <- create_arena(live=FALSE) %>% push_model(explainer) %>% push_observations(observations)
print(arena)
if (interactive()) upload_arena(arena)