Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
sentiment-classification
Languages:
English
Size:
1M - 10M
ArXiv:
License:
# coding=utf-8 | |
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor. | |
# | |
# 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 | |
# | |
# Unless required by applicable law or agreed to in writing, software | |
# distributed under the License is distributed on an "AS IS" BASIS, | |
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
# See the License for the specific language governing permissions and | |
# limitations under the License. | |
"""The amazon polarity dataset for text classification.""" | |
from __future__ import absolute_import, division, print_function | |
import csv | |
import os | |
import datasets | |
_CITATION = """\ | |
@inproceedings{mcauley2013hidden, | |
title={Hidden factors and hidden topics: understanding rating dimensions with review text}, | |
author={McAuley, Julian and Leskovec, Jure}, | |
booktitle={Proceedings of the 7th ACM conference on Recommender systems}, | |
pages={165--172}, | |
year={2013} | |
} | |
""" | |
_DESCRIPTION = """\ | |
The Amazon reviews dataset consists of reviews from amazon. | |
The data span a period of 18 years, including ~35 million reviews up to March 2013. | |
Reviews include product and user information, ratings, and a plaintext review. | |
""" | |
_HOMEPAGE = "https://registry.opendata.aws/" | |
_LICENSE = "Apache License 2.0" | |
_URLs = { | |
"amazon_polarity": "https://drive.google.com/u/0/uc?id=0Bz8a_Dbh9QhbaW12WVVZS2drcnM&export=download", | |
} | |
class AmazonPolarityConfig(datasets.BuilderConfig): | |
"""BuilderConfig for AmazonPolarity.""" | |
def __init__(self, **kwargs): | |
"""BuilderConfig for AmazonPolarity. | |
Args: | |
**kwargs: keyword arguments forwarded to super. | |
""" | |
super(AmazonPolarityConfig, self).__init__(**kwargs) | |
class AmazonPolarity(datasets.GeneratorBasedBuilder): | |
"""Amazon Polarity Classification Dataset.""" | |
VERSION = datasets.Version("3.0.0") | |
BUILDER_CONFIGS = [ | |
AmazonPolarityConfig( | |
name="amazon_polarity", version=VERSION, description="Amazon Polarity Classification Dataset." | |
), | |
] | |
def _info(self): | |
features = datasets.Features( | |
{ | |
"label": datasets.features.ClassLabel( | |
names=[ | |
"negative", | |
"positive", | |
] | |
), | |
"title": datasets.Value("string"), | |
"content": datasets.Value("string"), | |
} | |
) | |
return datasets.DatasetInfo( | |
description=_DESCRIPTION, | |
features=features, | |
supervised_keys=None, | |
homepage=_HOMEPAGE, | |
license=_LICENSE, | |
citation=_CITATION, | |
) | |
def _split_generators(self, dl_manager): | |
"""Returns SplitGenerators.""" | |
my_urls = _URLs[self.config.name] | |
data_dir = dl_manager.download_and_extract(my_urls) | |
return [ | |
datasets.SplitGenerator( | |
name=datasets.Split.TRAIN, | |
gen_kwargs={ | |
"filepath": os.path.join(data_dir, "amazon_review_polarity_csv", "train.csv"), | |
"split": "train", | |
}, | |
), | |
datasets.SplitGenerator( | |
name=datasets.Split.TEST, | |
gen_kwargs={ | |
"filepath": os.path.join(data_dir, "amazon_review_polarity_csv", "test.csv"), | |
"split": "test", | |
}, | |
), | |
] | |
def _generate_examples(self, filepath, split): | |
""" Yields examples. """ | |
with open(filepath, encoding="utf-8") as f: | |
data = csv.reader(f, delimiter=",", quoting=csv.QUOTE_ALL) | |
for id_, row in enumerate(data): | |
yield id_, { | |
"title": row[1], | |
"content": row[2], | |
"label": int(row[0]) - 1, | |
} | |