Correct minor CausalForestDML documenation issue

Signed-off-by: Keith Battocchi <kebatt@microsoft.com>

econml/dml/causal_forest.py

@@ -567,7 +567,7 @@ class CausalForestDML(_BaseDML):
  ate_ : ndarray of shape (n_outcomes, n_treatments)
  The average constant marginal treatment effect of each treatment for each outcome,
  averaged over the training data and with a doubly robust correction. Available only
- when `discrete_treatment=True` and `oob=True`.
+ when `discrete_treatment=True` and `drate=True`.
  ate_stderr_ : ndarray of shape (n_outcomes, n_treatments)
  The standard error of the `ate_` attribute.
  feature_importances_ : ndarray of shape (n_features,)
@@ -997,7 +997,7 @@ def att__inference(self, *, T):
  Inference results information for the `att_` attribute, which is the average
  constant marginal treatment effect of each treatment for each outcome, averaged
  over the training data treated with treatment T and with a doubly robust correction.
- Available only when `discrete_treatment=True` and `oob=True`.
+ Available only when `discrete_treatment=True` and `drate=True`.
  """
  return NormalInferenceResults(d_t=self._d_t[0] if self._d_t else 1,
  d_y=self._d_y[0] if self._d_y else 1,