from evalml.pipelines.components.transformers import Transformer
[docs]class TextTransformer(Transformer):
"""Base class for all transformers working with text features.
Arguments:
component_obj (obj): Third-party objects useful in component implementation. Defaults to None.
random_seed (int): Seed for the random number generator. Defaults to 0.
"""
def __init__(self, component_obj=None, random_seed=0, **kwargs):
parameters = {}
parameters.update(kwargs)
super().__init__(
parameters=parameters, component_obj=component_obj, random_seed=random_seed
)
def _get_text_columns(self, X):
"""Returns the ordered list of columns names in the input which have been designated as text columns."""
return list(X.ww.select("NaturalLanguage", return_schema=True).columns)