Multiple feature columns

[wschin]

The types of parameters are not clear. For example, for FFM, we have doc

    :param feature: see `Columns </nimbusml/concepts/columns>`_.
    :param label: see `Columns </nimbusml/concepts/columns>`_.
    :param weight: see `Columns </nimbusml/concepts/columns>`_.
    :param learning_rate: Determines the size of the step taken in the
        direction of the gradient in each step of the learning process.  This
        determines how fast or slow the learner converges on the optimal
        solution. If the step size is too big, you might overshoot the optimal
        solution.  If the step size is too small, training takes longer to
        converge to the best solution.
    ...

User may not have any idea about what input should be provided by reading those strings. It at least needs to specify that the type of feature is a list of string such as ['Hello' , 'World'] and the type of learning_rate is float.