plot.xspliner.RdThe method provides all plotting methods offered by 'xspliner' package. See plot_variable_transition and plot_model_comparison for more details.
# S3 method for xspliner plot(x, variable_names = NULL, model = NULL, plot_response = TRUE, plot_approx = TRUE, data = NULL, plot_data = FALSE, plot_deriv = FALSE, n_plots = 6, sort_by = NULL, use_coeff = TRUE, compare_with = list(), prediction_funs = list(function(object, newdata) predict(object, newdata)), ...)
| x | Object of class 'xspliner'. |
|---|---|
| variable_names | Names of predictors which transitions should be plotted. |
| model | Base model that xspliner is based on. |
| plot_response | If TRUE black box model response is drawn. |
| plot_approx | If TRUE black box model response approximation is drawn. |
| data | Training data used for building |
| plot_data | If TRUE raw data is drawn. |
| plot_deriv | If TRUE derivative of approximation is showed on plot. |
| n_plots | Threshold for number of plots when plotting all variables. |
| sort_by | When comparing models determines according to which model should observations be ordered. |
| use_coeff | If TRUE both PDP function and its approximation is scaled with corresponding surrogate model coefficient. |
| compare_with | Named list. Other models that should be compared with xspliner and |
| prediction_funs | Prediction functions that should be used in model comparison. |
| ... | Another arguments passed into model specific method. |