Upload 3 files

README.md

@@ -1,3 +1,27 @@
 ---
-license: cc-by-4.0
+language:
+- en
+tags:
+- letter
+- tabular_classification
+- multiclass_classification
+- binary_classification
+- UCI
+pretty_name: Letter
+task_categories:  # Full list at https://github.com/huggingface/hub-docs/blob/main/js/src/lib/interfaces/Types.ts
+- tabular-classification
+configs:
+- letter
 ---
+# Letter
+The [Letter dataset](https://archive-beta.ics.uci.edu/dataset/59/letter+recognition) from the [UCI repository](https://archive-beta.ics.uci.edu/).
+Letter recognition.
+
+# Configurations and tasks
+| **Configuration**     | **Task**                  | **Description**         |
+|-----------------------|---------------------------|-------------------------|
+| letter                | Multiclass classification.|                         |
+| A                     | Binary classification.    | Is this letter A?       |
+| B                     | Binary classification.    | Is this letter B?       |
+| C                     | Binary classification.    | Is this letter C?       |
+| ...                   | Binary classification.    | ...       |

letter.py

@@ -0,0 +1,205 @@
+"""Letter Dataset"""
+
+from typing import List
+from functools import partial
+import string
+
+import datasets
+
+import pandas
+
+
+VERSION = datasets.Version("1.0.0")
+
+_ENCODING_DICS = {
+	"letter": {letter: i for i, letter in zip(string.ascii_uppercase)}
+}
+
+DESCRIPTION = "Letter dataset."
+_HOMEPAGE = "https://archive-beta.ics.uci.edu/dataset/170/letter"
+_URLS = ("https://archive-beta.ics.uci.edu/dataset/170/letter")
+_CITATION = """
+@misc{misc_letter_recognition_59,
+  author       = {Slate,David},
+  title        = {{Letter Recognition}},
+  year         = {1991},
+  howpublished = {UCI Machine Learning Repository},
+  note         = {{DOI}: \\url{10.24432/C5ZP40}}
+}
+"""
+
+# Dataset info
+urls_per_split = {
+	"train": "https://huggingface.co/datasets/mstz/letter/resolve/main/letter.data"
+}
+features_types_per_config = {
+	"letter": {
+		"x-box": datasets.Value("int64"),
+		"y-box": datasets.Value("int64"),
+		"width": datasets.Value("int64"),
+		"high": datasets.Value("int64"),
+		"onpix": datasets.Value("int64"),
+		"x-bar": datasets.Value("int64"),
+		"y-bar": datasets.Value("int64"),
+		"x2bar": datasets.Value("int64"),
+		"y2bar": datasets.Value("int64"),
+		"xybar": datasets.Value("int64"),
+		"x2ybr": datasets.Value("int64"),
+		"xy2br": datasets.Value("int64"),
+		"x-ege": datasets.Value("int64"),
+		"xegvy": datasets.Value("int64"),
+		"y-ege": datasets.Value("int64"),
+		"yegvx": datasets.Value("int64"),
+		"letter": datasets.ClassLabel(num_classes=26)
+	}
+}
+for i, letter in enumerate(string.ascii_uppercase):
+	features_types_per_config[letter] = {
+		"x-box": datasets.Value("int64"),
+		"y-box": datasets.Value("int64"),
+		"width": datasets.Value("int64"),
+		"high": datasets.Value("int64"),
+		"onpix": datasets.Value("int64"),
+		"x-bar": datasets.Value("int64"),
+		"y-bar": datasets.Value("int64"),
+		"x2bar": datasets.Value("int64"),
+		"y2bar": datasets.Value("int64"),
+		"xybar": datasets.Value("int64"),
+		"x2ybr": datasets.Value("int64"),
+		"xy2br": datasets.Value("int64"),
+		"x-ege": datasets.Value("int64"),
+		"xegvy": datasets.Value("int64"),
+		"y-ege": datasets.Value("int64"),
+		"yegvx": datasets.Value("int64"),
+		"letter": datasets.ClassLabel(num_classes=2)
+	}
+
+features_per_config = {k: datasets.Features(features_types_per_config[k]) for k in features_types_per_config}
+
+
+class LetterConfig(datasets.BuilderConfig):
+	def __init__(self, **kwargs):
+		super(LetterConfig, self).__init__(version=VERSION, **kwargs)
+		self.features = features_per_config[kwargs["name"]]
+
+
+class Letter(datasets.GeneratorBasedBuilder):
+	# dataset versions
+	DEFAULT_CONFIG = "letter"
+	BUILDER_CONFIGS = [
+		LetterConfig(name="letter", description="Letter for multiclass classification."),		
+		LetterConfig(name="A", description="Letter for binary letter A classification."),
+		LetterConfig(name="B", description="Letter for binary letter B classification."),
+		LetterConfig(name="C", description="Letter for binary letter C classification."),
+		LetterConfig(name="D", description="Letter for binary letter D classification."),
+		LetterConfig(name="E", description="Letter for binary letter E classification."),
+		LetterConfig(name="F", description="Letter for binary letter F classification."),
+		LetterConfig(name="G", description="Letter for binary letter G classification."),
+		LetterConfig(name="H", description="Letter for binary letter H classification."),
+		LetterConfig(name="I", description="Letter for binary letter I classification."),
+		LetterConfig(name="J", description="Letter for binary letter J classification."),
+		LetterConfig(name="K", description="Letter for binary letter K classification."),
+		LetterConfig(name="L", description="Letter for binary letter L classification."),
+		LetterConfig(name="M", description="Letter for binary letter M classification."),
+		LetterConfig(name="N", description="Letter for binary letter N classification."),
+		LetterConfig(name="O", description="Letter for binary letter O classification."),
+		LetterConfig(name="P", description="Letter for binary letter P classification."),
+		LetterConfig(name="Q", description="Letter for binary letter Q classification."),
+		LetterConfig(name="R", description="Letter for binary letter R classification."),
+		LetterConfig(name="S", description="Letter for binary letter S classification."),
+		LetterConfig(name="T", description="Letter for binary letter T classification."),
+		LetterConfig(name="U", description="Letter for binary letter U classification."),
+		LetterConfig(name="V", description="Letter for binary letter V classification."),
+		LetterConfig(name="W", description="Letter for binary letter W classification."),
+		LetterConfig(name="X", description="Letter for binary letter X classification."),
+		LetterConfig(name="Y", description="Letter for binary letter Y classification."),
+		LetterConfig(name="Z", description="Letter for binary letter Z classification."),
+	]
+
+
+	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):
+		data = pandas.read_csv(filepath, header=None)
+		data = self.preprocess(data)
+
+		for row_id, row in data.iterrows():
+			data_row = dict(row)
+
+			yield row_id, data_row
+
+	def preprocess(self, data: pandas.DataFrame) -> pandas.DataFrame:
+		for feature in _ENCODING_DICS:
+			encoding_function = partial(self.encode, feature)
+			data.loc[:, feature] = data[feature].apply(encoding_function)
+		
+		if self.config.name == "A":
+			data.letter = data.letter.apply(lambda x: 1 if x == 0 else 0)
+		elif self.config.name == "B":
+			data.letter = data.letter.apply(lambda x: 1 if x == 1 else 0)
+		elif self.config.name == "C":
+			data.letter = data.letter.apply(lambda x: 1 if x == 2 else 0)
+		elif self.config.name == "D":
+			data.letter = data.letter.apply(lambda x: 1 if x == 3 else 0)
+		elif self.config.name == "E":
+			data.letter = data.letter.apply(lambda x: 1 if x == 4 else 0)
+		elif self.config.name == "F":
+			data.letter = data.letter.apply(lambda x: 1 if x == 5 else 0)
+		elif self.config.name == "G":
+			data.letter = data.letter.apply(lambda x: 1 if x == 6 else 0)
+		elif self.config.name == "H":
+			data.letter = data.letter.apply(lambda x: 1 if x == 7 else 0)
+		elif self.config.name == "I":
+			data.letter = data.letter.apply(lambda x: 1 if x == 8 else 0)
+		elif self.config.name == "J":
+			data.letter = data.letter.apply(lambda x: 1 if x == 9 else 0)
+		elif self.config.name == "K":
+			data.letter = data.letter.apply(lambda x: 1 if x == 10 else 0)
+		elif self.config.name == "L":
+			data.letter = data.letter.apply(lambda x: 1 if x == 11 else 0)
+		elif self.config.name == "M":
+			data.letter = data.letter.apply(lambda x: 1 if x == 12 else 0)
+		elif self.config.name == "N":
+			data.letter = data.letter.apply(lambda x: 1 if x == 13 else 0)
+		elif self.config.name == "O":
+			data.letter = data.letter.apply(lambda x: 1 if x == 14 else 0)
+		elif self.config.name == "P":
+			data.letter = data.letter.apply(lambda x: 1 if x == 15 else 0)
+		elif self.config.name == "Q":
+			data.letter = data.letter.apply(lambda x: 1 if x == 16 else 0)
+		elif self.config.name == "R":
+			data.letter = data.letter.apply(lambda x: 1 if x == 17 else 0)
+		elif self.config.name == "S":
+			data.letter = data.letter.apply(lambda x: 1 if x == 18 else 0)
+		elif self.config.name == "T":
+			data.letter = data.letter.apply(lambda x: 1 if x == 19 else 0)
+		elif self.config.name == "U":
+			data.letter = data.letter.apply(lambda x: 1 if x == 20 else 0)
+		elif self.config.name == "V":
+			data.letter = data.letter.apply(lambda x: 1 if x == 21 else 0)
+		elif self.config.name == "W":
+			data.letter = data.letter.apply(lambda x: 1 if x == 22 else 0)
+		elif self.config.name == "X":
+			data.letter = data.letter.apply(lambda x: 1 if x == 23 else 0)
+		elif self.config.name == "Y":
+			data.letter = data.letter.apply(lambda x: 1 if x == 24 else 0)
+		elif self.config.name == "Z":
+			data.letter = data.letter.apply(lambda x: 1 if x == 25 else 0)
+				
+		return data[list(features_types_per_config[self.config.name].keys())]
+
+	def encode(self, feature, value):
+		if feature in _ENCODING_DICS:
+			return _ENCODING_DICS[feature][value]
+		raise ValueError(f"Unknown feature: {feature}")