Variable Importance
Dashboard options
- Maximum variables in Variable Importance
- Display boxplots over Variable Importance
- Left margin for variables names with values
Connector options
# Size of random subset. For large datasets can speedup calculations.
# Use None to select whole dataset.
arena.set_option('FeatureImportance', 'N', None)
# Number of permutations.
arena.set_option('FeatureImportance', 'B', 10)Partial Dependence
Dashboard options
- Left margin for variables values - for categorical variables
Connector options
# Method of selecting points: 'quantile' or 'uniform'
arena.set_option('PartialDependence', 'grid_type', 'quantile')
# Maximum number of points for profile. Final number can
# be lower using 'quantile' method.
arena.set_option('PartialDependence', 'grid_points', 101)
# Size of random subset. For large datasets can speedup calculations.
# Use None to select whole dataset.
arena.set_option('PartialDependence', 'N', 500)Accumulated Dependence
Dashboard options
- Left margin for variables values - for categorical variables
Connector options
# Method of selecting points: 'quantile' or 'uniform'
arena.set_option('AccumulatedDependence', 'grid_type', 'quantile')
# Maximum number of points for profile. Final number can
# be lower using 'quantile' method.
arena.set_option('AccumulatedDependence', 'grid_points', 101)
# Size of random subset. For large datasets can speedup calculations.
# Use None to select whole dataset.
arena.set_option('AccumulatedDependence', 'N', 500)