deploy: braindecode/braindecode@b0f345a

Author: adammounir

dev/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip

@@ -144,7 +144,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "## Training\nIn difference to trialwise decoding, we now should supply\n``cropped=True`` to the :class:`EEGClassifer\n<braindecode.classifier.EEGClassifier>`, and :class:`CroppedLoss\n<braindecode.training.CroppedLoss>` as the criterion,\nas well as ``criterion__loss_function`` as the loss function\napplied to the meaned predictions.\n\n<div class=\"alert alert-info\"><h4>Note</h4><p>In this tutorial, we use some default parameters that we\n    have found to work well for motor decoding, however we strongly\n    encourage you to perform your own hyperparameter optimization using\n    cross validation on your training data.</p></div>\n\n\n"
+        "## Training\nIn difference to trialwise decoding, we now should supply\n``cropped=True`` to the :class:`EEGClassifier\n<braindecode.classifier.EEGClassifier>`, and :class:`CroppedLoss\n<braindecode.training.CroppedLoss>` as the criterion,\nas well as ``criterion__loss_function`` as the loss function\napplied to the meaned predictions.\n\n<div class=\"alert alert-info\"><h4>Note</h4><p>In this tutorial, we use some default parameters that we\n    have found to work well for motor decoding, however we strongly\n    encourage you to perform your own hyperparameter optimization using\n    cross validation on your training data.</p></div>\n\n\n"
       ]
     },
     {