Additivity check fails with XGBoost

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Hi,

when using XGB, the additivity check fails, while it does not when using native shap or lightgbm
Using `xgboost 1.7.6, shap 0.41.0 and fasttreeshap 0.1.6`

could it be linked to https://github.com/linkedin/FastTreeSHAP/issues/15 ?

example (changing `algorithm` or `feature_perturbation` lead to the same error):

```python
from sklearn.datasets import make_regression
from xgboost import XGBRegressor
from lightgbm import LGBMRegressor
from fasttreeshap import TreeExplainer as FastTreeExplainer

X, y = make_regression(n_samples=1000, n_features=10, n_informative=8, noise=1, random_state=8)
model = XGBRegressor() #LGBMRegressor()
model.fit(X, y)
explainer = FastTreeExplainer(model, algorithm="auto", shortcut=False, feature_perturbation="tree_path_dependent")
shap_matrix = explainer.shap_values(X)
```

```
Exception: Additivity check failed in TreeExplainer! Please ensure [...]
```

The following runs fine

```python
explainer = shap.TreeExplainer(model, feature_perturbation="tree_path_dependent")
shap_values = explainer.shap_values(X)
```
Thanks

Start by running the reported XGBRegressor example with xgboost 1.7.6, shap 0.41.0, and fasttreeshap 0.1.6, then compare it with the native SHAP and LightGBM cases. Inspect fasttreeshap.TreeExplainer's additivity-check path and its XGBoost handling, including the linked issue, to identify why the check fails. Done means the XGBoost example completes without the additivity exception while the check remains valid.

Written by the indexing model from the issue text.