Datasets:
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"""Victorian."""
from typing import List
from functools import partial
import datasets
import pandas
VERSION = datasets.Version("1.0.0")
_ORIGINAL_FEATURE_NAMES = [
"text",
"author"
]
_BASE_FEATURE_NAMES = [
"text",
"author"
]
DESCRIPTION = "Victorian dataset from the Gungor thesis.\"."
_HOMEPAGE = "https://scholarworks.iupui.edu/server/api/core/bitstreams/708a9870-915e-4d59-b54d-938af563c196/content"
_URLS = ("https://scholarworks.iupui.edu/server/api/core/bitstreams/708a9870-915e-4d59-b54d-938af563c196/content")
_CITATION = """
@phdthesis{gungor2018benchmarking,
title={Benchmarking authorship attribution techniques using over a thousand books by fifty victorian era novelists},
author={Gungor, Abdulmecit},
year={2018},
school={Purdue University}
}"""
# Dataset info
urls_per_split = {
"train": "https://huggingface.co/datasets/mstz/victorian_authorship/resolve/main/train.csv",
}
features_types_per_config = {
"authorship": {
"text": datasets.Value("string"),
"author": datasets.ClassLabel(num_classes=51)
}
}
features_per_config = {k: datasets.Features(features_types_per_config[k]) for k in features_types_per_config}
class VictorianConfig(datasets.BuilderConfig):
def __init__(self, **kwargs):
super(VictorianConfig, self).__init__(version=VERSION, **kwargs)
self.features = features_per_config[kwargs["name"]]
class Victorian(datasets.GeneratorBasedBuilder):
# dataset versions
DEFAULT_CONFIG = "authorship"
BUILDER_CONFIGS = [
VictorianConfig(name="authorship",
description="authorship"),
]
def _info(self):
info = datasets.DatasetInfo(description=DESCRIPTION, citation=_CITATION, homepage=_HOMEPAGE,
features=features_per_config[self.config.name])
return info
def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
downloads = dl_manager.download_and_extract(urls_per_split)
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloads["train"]})
]
def _generate_examples(self, filepath: str):
print(f"reading {filepath}")
data = pandas.read_csv(filepath, encoding="latin-1")
print(data.columns)
for row_id, row in data.iterrows():
data_row = dict(row)
yield row_id, data_row
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