Preprocessing function that makes one-hot encoding.
One-hot encoding maps a categorical feature,
represented as a label index (Double or String value),
to a binary vector with at most a single one-value indicating the presence of a specific feature value
from among the set of all feature values.
This preprocessor can transform multiple columns which indices are handled during training process.
Each one-hot encoded binary vector adds its cells to the end of the current feature vector according the order of handled categorial features.