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.gitattributes

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 *.jpg filter=lfs diff=lfs merge=lfs -text
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+test.csv filter=lfs diff=lfs merge=lfs -text
+train.csv filter=lfs diff=lfs merge=lfs -text

test.csv

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b8ebb429790d3639c17cd5f11c05b4fefb82ae51ae3ae14a6638d1b623630091
+size 265585562

train.csv

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+version https://git-lfs.github.com/spec/v1
+oid sha256:66136afe6b911e8777e934b5a92351f1ade17e9c5265f98d43f2f67048f3dffe
+size 193572713

victorian_authorship.py

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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/raw/main/train.csv",
+    "test": "https://huggingface.co/datasets/mstz/victorian_authorship/raw/main/test.csv",
+}
+features_types_per_config = {
+    "authorship": {
+        "text": datasets.Value("string"),
+        "author": datasets.ClassLabel(num_classes=50)
+    }
+}
+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"]}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloads["test"]})
+        ]
+    
+    def _generate_examples(self, filepath: str):       
+        data = pandas.read_csv(filepath, header=None)
+        data.columns = _BASE_FEATURE_NAMES
+
+        for row_id, row in data.iterrows():
+            data_row = dict(row)
+
+            yield row_id, data_row