Datasets:
sms_spam

	# coding=utf-8
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	#
	# Licensed under the Apache License, Version 2.0 (the "License");
	# you may not use this file except in compliance with the License.
	# You may obtain a copy of the License at
	#
	# http://www.apache.org/licenses/LICENSE-2.0
	#
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	# Lint as: python3
	"""SMS Spam Collection Data Set"""


	import os

	import datasets
	from datasets.tasks import TextClassification


	_CITATION = """\
	@inproceedings{Almeida2011SpamFiltering,
	title={Contributions to the Study of SMS Spam Filtering: New Collection and Results},
	author={Tiago A. Almeida and Jose Maria Gomez Hidalgo and Akebo Yamakami},
	year={2011},
	booktitle = "Proceedings of the 2011 ACM Symposium on Document Engineering (DOCENG'11)",
	}
	"""

	_DESCRIPTION = """\
	The SMS Spam Collection v.1 is a public set of SMS labeled messages that have been collected for mobile phone spam research.
	It has one collection composed by 5,574 English, real and non-enconded messages, tagged according being legitimate (ham) or spam.
	"""

	_DATA_URL = "http://archive.ics.uci.edu/ml/machine-learning-databases/00228/smsspamcollection.zip"


	class SmsSpam(datasets.GeneratorBasedBuilder):
	"""SMS Spam Collection Data Set"""

	BUILDER_CONFIGS = [
	datasets.BuilderConfig(
	name="plain_text",
	version=datasets.Version("1.0.0", ""),
	description="Plain text import of SMS Spam Collection Data Set",
	)
	]

	def _info(self):
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(
	{
	"sms": datasets.Value("string"),
	"label": datasets.features.ClassLabel(names=["ham", "spam"]),
	}
	),
	supervised_keys=("sms", "label"),
	homepage="http://archive.ics.uci.edu/ml/datasets/SMS+Spam+Collection",
	citation=_CITATION,
	task_templates=[TextClassification(text_column="sms", label_column="label")],
	)

	def _split_generators(self, dl_manager):
	dl_dir = dl_manager.download_and_extract(_DATA_URL)
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN, gen_kwargs={"filepath": os.path.join(dl_dir, "SMSSpamCollection")}
	),
	]

	def _generate_examples(self, filepath):
	"""This function returns the examples in the raw (text) form."""

	with open(filepath, encoding="utf-8") as sms_file:
	for idx, line in enumerate(sms_file):
	fields = line.split("\t")

	if fields[0] == "ham":
	label = 0
	else:
	label = 1

	yield idx, {
	"sms": fields[1],
	"label": label,
	}