class_docstr: An sklearn classifier adapter for fasttext that takes input by index.
  
  Parameters
  ----------
  input_ix : int
      The index of the text input column for fasttext.
  **kwargs
      Additional keyword arguments will be redirected to
      fasttext.train_supervised.
class_docstr_tok: ["An","sklearn","classifier","adapter","for","fasttext","that","takes","input","by","index",".","Parameters","--","--","--","--","--","input_ix",":","int","The","index","of","the","text","input","column","for","fasttext",".","*","*","kwargs","Additional","keyword","arguments","will","be","redirected","to","fasttext.train_supervised","."]
docstr: Get parameters for this estimator.
  Parameters
  ----------
  deep : boolean, optional
      If True, will return the parameters for this estimator and
      contained subobjects that are estimators.
  Returns
  -------
  params : mapping of string to any
      Parameter names mapped to their values.
docstr_tok: ["Get","parameters","for","this","estimator",".","Parameters","--","--","--","--","--","deep",":","boolean",",","optional","If","True",",","will","return","the","parameters","for","this","estimator","and","contained","subobjects","that","are","estimators",".","Returns","--","--","--","-","params",":","mapping","of","string","to","any","Parameter","names","mapped","to","their","values","."]
code: def get_params(self, deep=True):
      """Get parameters for this estimator.
      Parameters
      ----------
      deep : boolean, optional
          If True, will return the parameters for this estimator and
          contained subobjects that are estimators.
      Returns
      -------
      params : mapping of string to any
          Parameter names mapped to their values.
      """
      # re-implementation that will preserve ft kwargs
      return {"input_ix": self.input_ix, **self.kwargs}
  
imports: import os
  import abc
  import numpy
  from fasttext import train_supervised
  from sklearn.base import BaseEstimator, ClassifierMixin
  from sklearn.utils.multiclass import unique_labels
  from sklearn.exceptions import NotFittedError
  from .util import temp_dataset_fpath, dump_xy_to_fasttext_format, python_fasttext_model_to_bytes, bytes_to_python_fasttext_model
label_desc: Use image node_id 3 for calling the IdxBasedFtClassifier obj's underlying member method code with example usage: obj.get_params(deep) and returns: dict