class_docstr: SMS Spam Collection dataset.
  
  The data contains 5,574 items and 1 feature (i.e. SMS body). Spam messages represent
  13.4% of the dataset. The goal is to predict whether an SMS is a spam or not.
  
  References
  ----------
  [^1]: [Almeida, T.A., Hidalgo, J.M.G. and Yamakami, A., 2011, September. Contributions to the study of SMS spam filtering: new collection and results. In Proceedings of the 11th ACM symposium on Document engineering (pp. 259-262).](http://www.dt.fee.unicamp.br/~tiago/smsspamcollection/doceng11.pdf)
class_docstr_tok: ["SMS","Spam","Collection","dataset",".","The","data","contains","5,574","items","and","1","feature","(","i.e",".","SMS","body",")",".","Spam","messages","represent","13.4","%","of","the","dataset",".","The","goal","is","to","predict","whether","an","SMS","is","a","spam","or","not",".","References","--","--","--","--","--","[","^1","]",":","[","Almeida",",","T.A.",",","Hidalgo",",","J.M.G",".","and","Yamakami",",","A.",",","2011",",","September",".","Contributions","to","the","study","of","SMS","spam","filtering",":","new","collection","and","results",".","In","Proceedings","of","the","11th","ACM","symposium","on","Document","engineering","(","pp",".","259-262",")",".","]","(","http",":","\/\/www.dt.fee.unicamp.br\/~tiago\/smsspamcollection\/doceng11.pdf",")"]
code: def _iter(self):
      with open(self.path) as f:
          for row in f:
              label, body = row.split("\t")
              yield ({"body": body}, label == "spam")
  
imports: from __future__ import annotations
  from .None import base
label_desc: Use image node_id 2 for calling the SMSSpam obj's underlying member method code with example usage: obj._iter() without return types