Create LabelBinarizer.md

Author: DragonflyStats

LabelBinarizer.md

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+Binarize labels in a one-vs-all fashion
+
+Several regression and binary classification algorithms are available in the scikit. A simple way to extend these algorithms to the multi-class classification case is to use the so-called one-vs-all scheme.
+At learning time, this simply consists in learning one regressor or binary classifier per class. 
+
+In doing so, one needs to convert multi-class labels to binary labels (belong or does not belong to the class). 
+
+LabelBinarizer makes this process easy with the transform method.
+At prediction time, one assigns the class for which the corresponding model gave the greatest confidence. 
+
+LabelBinarizer makes this easy with the inverse_transform method.