Fix docs for NumPy 2 (#59)

docs/user_guide/fit_predict.rst

@@ -61,7 +61,7 @@ The default quantiles can be overwritten at prediction time by specifying a valu
 The output of the `predict` method is an array with one column for each specified quantile or a single column if no quantiles are specified. The order of the output columns corresponds to the order of the quantiles, which can be specified in any order (i.e., they do not need to be monotonically ordered)::
 
     >>> y_pred = reg.predict(X_test, quantiles=[0.5, 0.25, 0.75])
-    >>> (y_pred[:, 0] >= y_pred[:, 1]).all()
+    >>> bool((y_pred[:, 0] >= y_pred[:, 1]).all())
     True
 
 Multi-target quantile regression is also supported. If the target values are multi-dimensional, then the second output column will correspond to the number of targets::