h2o-py/h2o/h2o.py
def interaction(data, factors, pairwise, max_factors, min_occurrence, destination_frame=None):
    """
    Categorical Interaction Feature Creation in H2O.

    Creates a frame in H2O with n-th order interaction features between categorical columns, as specified by
    the user.

    :param data: the H2OFrame that holds the target categorical columns.
    :param factors: factor columns (either indices or column names).
    :param pairwise: If True, create pairwise interactions between factors (otherwise create one
        higher-order interaction). Only applicable if there are 3 or more factors.
    :param max_factors: Max. number of factor levels in pair-wise interaction terms (if enforced, one extra
        catch-all factor will be made).
    :param min_occurrence: Min. occurrence threshold for factor levels in pair-wise interaction terms
    :param destination_frame: a string indicating the destination key. If empty, this will be auto-generated by H2O.

    :returns: :class:`H2OFrame`
    """
    assert_is_type(data, H2OFrame)
    assert_is_type(factors, [str, int])
    assert_is_type(pairwise, bool)
    assert_is_type(max_factors, int)
    assert_is_type(min_occurrence, int)
    assert_is_type(destination_frame, str, None)
    factors = [data.names[n] if is_type(n, int) else n for n in factors]
    parms = {"dest": py_tmp_key(append=h2oconn.session_id) if destination_frame is None else destination_frame,
             "source_frame": data.frame_id,
             "factor_columns": [quoted(f) for f in factors],
             "pairwise": pairwise,
             "max_factors": max_factors,
             "min_occurrence": min_occurrence,
             }
    H2OJob(api("POST /3/Interaction", data=parms), "Interactions").poll()
    return get_frame(parms["dest"])
def interaction(data, factors, pairwise, max_factors, min_occurrence, destination_frame=None):
    """
    Categorical Interaction Feature Creation in H2O.

    Creates a frame in H2O with n-th order interaction features between categorical columns, as specified by
    the user.

    :param data: the H2OFrame that holds the target categorical columns.
    :param factors: factor columns (either indices or column names).
    :param pairwise: If True, create pairwise interactions between factors (otherwise create one
        higher-order interaction). Only applicable if there are 3 or more factors.
    :param max_factors: Max. number of factor levels in pair-wise interaction terms (if enforced, one extra
        catch-all factor will be made).
    :param min_occurrence: Min. occurrence threshold for factor levels in pair-wise interaction terms
    :param destination_frame: a string indicating the destination key. If empty, this will be auto-generated by H2O.

    :returns: :class:`H2OFrame`
    """
    assert_is_type(data, H2OFrame)
    assert_is_type(factors, [str, int])
    assert_is_type(pairwise, bool)
    assert_is_type(max_factors, int)
    assert_is_type(min_occurrence, int)
    assert_is_type(destination_frame, str, None)
    factors = [data.names[n] if is_type(n, int) else n for n in factors]
    parms = {"dest": py_tmp_key(append=h2oconn.session_id) if destination_frame is None else destination_frame,
             "source_frame": data.frame_id,
             "factor_columns": [quoted(f) for f in factors],
             "pairwise": pairwise,
             "max_factors": max_factors,
             "min_occurrence": min_occurrence,
             }
    H2OJob(api("POST /3/Interaction", data=parms), "Interactions").poll()
    return get_frame(parms["dest"])
def interaction ( data , factors , pairwise , max_factors , min_occurrence , destination_frame = None ) : assert_is_type ( data , H2OFrame ) assert_is_type ( factors , [ str , int ] ) assert_is_type ( pairwise , bool ) assert_is_type ( max_factors , int ) assert_is_type ( min_occurrence , int ) assert_is_type ( destination_frame , str , None ) factors = [ data . names [ n ] if is_type ( n , int ) else n for n in factors ] parms = { "dest" : py_tmp_key ( append = h2oconn . session_id ) if destination_frame is None else destination_frame , "source_frame" : data . frame_id , "factor_columns" : [ quoted ( f ) for f in factors ] , "pairwise" : pairwise , "max_factors" : max_factors , "min_occurrence" : min_occurrence , } H2OJob ( api ( "POST /3/Interaction" , data = parms ) , "Interactions" ) . poll ( ) return get_frame ( parms [ "dest" ] )
Categorical Interaction Feature Creation in H2O.

    Creates a frame in H2O with n-th order interaction features between categorical columns, as specified by
    the user.

    :param data: the H2OFrame that holds the target categorical columns.
    :param factors: factor columns (either indices or column names).
    :param pairwise: If True, create pairwise interactions between factors (otherwise create one
        higher-order interaction). Only applicable if there are 3 or more factors.
    :param max_factors: Max. number of factor levels in pair-wise interaction terms (if enforced, one extra
        catch-all factor will be made).
    :param min_occurrence: Min. occurrence threshold for factor levels in pair-wise interaction terms
    :param destination_frame: a string indicating the destination key. If empty, this will be auto-generated by H2O.

    :returns: :class:`H2OFrame`
Categorical Interaction Feature Creation in H2O .