Update docs/source/usage.rst

Co-authored-by: Steffen Schneider <[email protected]>

Author: MMathisLab

docs/source/usage.rst

@@ -1235,8 +1235,9 @@ Putting all previous snippet examples together, we obtain the following pipeline
     from sklearn.model_selection import train_test_split
 
     split_idx = int(0.8 * len(neural_data)) 
-    #suggest: 5%-20% depending on your dataset size; note this also split 
-             early/late, which might not be ideal for your data/expt!
+    # suggestion: 5%-20% depending on your dataset size; note that this splits the
+    # into an early and late part, which might not be ideal for your data/experiment!
+    # As a more involved alternative, consider e.g. a nested time-series split.
 
     train_data = neural_data[:split_idx]
     valid_data = neural_data[split_idx:]