Minor update

Author: GraemeMalcolm

03 - Classification.ipynb

@@ -633,7 +633,7 @@
     "    - *circle* or *hexagon*\n",
     "    - *triangle* or *hexagon*\n",
     "\n",
-    "In both approaches, the overall model that combines the classifiers generates a vector of predictions in which the probabilities generated from the classifiers are used to determine which class to predict, so a prediction for *circle* would be \\[0,1,0,0\\]\n",
+    "In both approaches, the overall model that combines the classifiers generates a vector of predictions in which the probabilities generated from the individual binary classifiers are used to determine which class to predict.\n",
     "\n",
     "Fortunately, in most machine learning frameworks, including scikit-learn, implementing a multiclass classification model is not significantly more complex than binary classification - and in most cases, the estimators used for binary classification implicitly support multiclass classification by abstracting an OVR algorithm, an OVO algorithm, or by allowing a choice of either.\n",
     "\n",