Feature/feature hasher

FeatureHasher added as an alternative to DictVectorizer.

Added 2 parameters in config file in Input part:

* feature_hasher = true, could be true or false. By default it is False (works as DictVectorizer)
* hasher_features = 5 (Number of features used in the feature_hasher, at least should be the number of features among all files.)

Please replace these sections with the following:

```rst
    **feature_hasher** *(Optional)*
        If "true", this enables a high-speed, low-memory vectorizer that uses
        feature hashing for converting feature dictionaries into NumPy arrays
        instead of using a ``DictVectorizer``.  This flag will drastically
        reduce memory consumption for data sets with a large number of features.
        If enabled, the user should also specify the number of features in the
        ``hasher_features`` field.  For addition information see
        `the scikit-learn documentation <http://scikit-learn.org/stable/modules/feature_extraction.html#feature-hashing>`_.

    **hasher_features** *(Optional)*
        The number of features used by the ``FeatureHasher`` if the
        ``feature_hasher`` flag is enabled.  It is suggested to use the power of
        two larger than the number of features in the data set. For example, if
        you had 17 features, you would want to set the flag to 32.
```