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  1. ttc4900.py +0 -130
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- # coding=utf-8
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- # Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
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- #
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- # Licensed under the Apache License, Version 2.0 (the "License");
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- # you may not use this file except in compliance with the License.
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- # You may obtain a copy of the License at
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- #
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- # http://www.apache.org/licenses/LICENSE-2.0
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- #
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- # Unless required by applicable law or agreed to in writing, software
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- # distributed under the License is distributed on an "AS IS" BASIS,
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- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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- # See the License for the specific language governing permissions and
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- # limitations under the License.
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- # Lint as: python3
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- """TTC4900: A Benchmark Data for Turkish Text Categorization"""
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-
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-
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- import csv
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-
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- import datasets
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- from datasets.tasks import TextClassification
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-
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-
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- logger = datasets.logging.get_logger(__name__)
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-
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-
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- _DESCRIPTION = """\
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- The data set is taken from kemik group
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- http://www.kemik.yildiz.edu.tr/
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- The data are pre-processed for the text categorization, collocations are found, character set is corrected, and so forth.
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- We named TTC4900 by mimicking the name convention of TTC 3600 dataset shared by the study http://journals.sagepub.com/doi/abs/10.1177/0165551515620551
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-
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- If you use the dataset in a paper, please refer https://www.kaggle.com/savasy/ttc4900 as footnote and cite one of the papers as follows:
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-
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- - A Comparison of Different Approaches to Document Representation in Turkish Language, SDU Journal of Natural and Applied Science, Vol 22, Issue 2, 2018
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- - A comparative analysis of text classification for Turkish language, Pamukkale University Journal of Engineering Science Volume 25 Issue 5, 2018
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- - A Knowledge-poor Approach to Turkish Text Categorization with a Comparative Analysis, Proceedings of CICLING 2014, Springer LNCS, Nepal, 2014.
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- """
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-
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- _CITATION = """\
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- @article{doi:10.5505/pajes.2018.15931,
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- author = {Yıldırım, Savaş and Yıldız, Tuğba},
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- title = {A comparative analysis of text classification for Turkish language},
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- journal = {Pamukkale Univ Muh Bilim Derg},
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- volume = {24},
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- number = {5},
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- pages = {879-886},
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- year = {2018},
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- doi = {10.5505/pajes.2018.15931},
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- note ={doi: 10.5505/pajes.2018.15931},
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-
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- URL = {https://dx.doi.org/10.5505/pajes.2018.15931},
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- eprint = {https://dx.doi.org/10.5505/pajes.2018.15931}
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- }
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- """
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-
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- _LICENSE = "CC0: Public Domain"
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- _HOMEPAGE = "https://www.kaggle.com/savasy/ttc4900"
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- _DOWNLOAD_URL = "https://raw.githubusercontent.com/savasy/TurkishTextClassification/master"
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- _FILENAME = "7allV03.csv"
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-
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-
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- class TTC4900Config(datasets.BuilderConfig):
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- """BuilderConfig for TTC4900"""
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-
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- def __init__(self, **kwargs):
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- """BuilderConfig for TTC4900.
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- Args:
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- **kwargs: keyword arguments forwarded to super.
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- """
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- super(TTC4900Config, self).__init__(**kwargs)
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-
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-
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- class TTC4900(datasets.GeneratorBasedBuilder):
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- """TTC4900: A Benchmark Data for Turkish Text Categorization"""
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-
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- BUILDER_CONFIGS = [
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- TTC4900Config(
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- name="ttc4900",
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- version=datasets.Version("1.0.0"),
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- description="A Benchmark Data for Turkish Text Categorization",
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- ),
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- ]
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-
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- def _info(self):
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- return datasets.DatasetInfo(
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- description=_DESCRIPTION,
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- features=datasets.Features(
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- {
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- "category": datasets.features.ClassLabel(
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- names=["siyaset", "dunya", "ekonomi", "kultur", "saglik", "spor", "teknoloji"]
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- ),
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- "text": datasets.Value("string"),
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- }
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- ),
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- supervised_keys=None,
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- # Homepage of the dataset for documentation
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- homepage=_HOMEPAGE,
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- # License for the dataset if available
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- license=_LICENSE,
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- # Citation for the dataset
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- citation=_CITATION,
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- task_templates=[TextClassification(text_column="text", label_column="category")],
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- )
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-
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- def _split_generators(self, dl_manager):
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- """Returns SplitGenerators."""
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-
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- urls_to_download = {
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- "train": _DOWNLOAD_URL + "/" + _FILENAME,
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- }
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- downloaded_files = dl_manager.download(urls_to_download)
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- return [
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- datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
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- ]
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-
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- def _generate_examples(self, filepath):
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- """Generate TTC4900 examples."""
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- logger.info("⏳ Generating examples from = %s", filepath)
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- with open(filepath, encoding="utf-8") as f:
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- rdr = csv.reader(f, delimiter=",")
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- next(rdr)
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- rownum = 0
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- for row in rdr:
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- rownum += 1
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- yield rownum, {
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- "category": row[0],
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- "text": row[1],
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- }