Plots for categorical splits don't show named categories

[david-cortes]

When producing a plot of a tree with categorical splits, the plots will use the numbers of the categories:

import numpy as np, xgboost as xgb
rng = np.random.default_rng(seed=123)
X = rng.integers(4, size=(100,3))
y = rng.standard_normal(size=100)
dm = xgb.DMatrix(
    data=X,
    label=y,
    feature_types=["c"]*3
)
model = xgb.train(
    dtrain=dm,
    params={
        "tree_method" : "hist",
        "max_depth" : 2
    },
    num_boost_round=3
)
xgb.plot_tree(model)

Categorical features typically have named categories. Would be quite helpful to show those on the plots instead of the numbers, which might not be easy to mentally map to a given category.

For this, I guess that a potential solution could be to add an additional dmatrix/booster string attribure for "categorical_names" or so, like there is a "feature_name".

[trivialfis]

XGBoost takes encoded categories instead of raw data, as a result, there's no name for them. We need to think of a way to pass the information from the encoder to XGB