class_docstr: Create a ``FeatureSet`` instance from an ARFF file.
  
  If example/instance IDs are included in the files, they
  must be specified in the ``id`` column.
  Also, there must be a column with the name specified by ``label_col`` if the
  data is labeled, and this column must be the final one (as it is in Weka).
  
  Parameters
  ----------
  path_or_list : Union[:class:`skll.types.PathOrStr`, List[Dict[str, Any]]]
      The path to the ARFF file.
  
  kwargs : Optional[Dict[str, Any]]
      Other arguments to the Reader object.
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docstr: Initialize ARFFReader class.
docstr_tok: ["Initialize","ARFFReader","class","."]
code: def __init__(
      self,
      path_or_list: Union[PathOrStr, List[Dict[str, Any]]],
      **kwargs,
  ):
      """Initialize ARFFReader class."""
      super(ARFFReader, self).__init__(path_or_list, **kwargs)
      self.dialect = "arff"
      self.relation = ""
      self.regression = False
  
imports: import csv
  import json
  import logging
  import re
  import sys
  from io import StringIO
  from itertools import chain
  from numbers import Number
  from pathlib import Path
  from typing import IO, Any, Dict, List, Optional, Tuple, Union
  import numpy
  import pandas
  from bs4 import UnicodeDammit
  from sklearn.feature_extraction import FeatureHasher
  from skll.data import FeatureSet
  from skll.data.dict_vectorizer import DictVectorizer
  from skll.types import ClassMap, FeatGenerator, FeatureDictList, IdType, LabelType, PathOrStr
label_desc: Use image node_id 1 to create a new ARFFReader object from inherited base classes: Reader with example: obj = ARFFReader(path_or_list)