In many applications, it is convenient to transform categorical (non-numerical) features into numerical variables. For instance, the categorical feature digit with the value d in [0-9] can be encoded into a binary vector with 10 positions, which always has 0 value, except the d-th position where a 1 is present. This type of representation is called one-hot encoding (OHE) and is very common in data mining when the learning algorithm is specialized for dealing with numerical functions.
One-hot encoding — OHE
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