MNT Use float64 epsilon when clipping initial probabilities in GradientBoosting (scikit-learn#31575)

Co-authored-by: Jérémie du Boisberranger <jeremie@probabl.ai>

Author: mohiuddin-khan-shiam

sklearn/ensemble/_gb.py

@@ -114,7 +114,7 @@ def _init_raw_predictions(X, estimator, loss, use_predict_proba):
         predictions = estimator.predict_proba(X)
         if not loss.is_multiclass:
             predictions = predictions[:, 1]  # probability of positive class
-        eps = np.finfo(np.float32).eps  # FIXME: This is quite large!
+        eps = np.finfo(np.float64).eps
         predictions = np.clip(predictions, eps, 1 - eps, dtype=np.float64)
     else:
         predictions = estimator.predict(X).astype(np.float64)