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README.md

@@ -1,3 +1,33 @@
 ---
-license: cc-by-4.0
+language:
+- en
+tags:
+- isolet
+- tabular_classification
+- binary_classification
+- multiclass_classification
+pretty_name: Isolet
+size_categories:
+- 1K<n<10K
+task_categories:  # Full list at https://github.com/huggingface/hub-docs/blob/main/js/src/lib/interfaces/Types.ts
+- tabular-classification
+configs:
+- isolet
+
 ---
+# Isolet
+The [Isolet dataset](https://archive-beta.ics.uci.edu/dataset/54/isolet) from the [UCI ML repository](https://archive.ics.uci.edu/ml/datasets).
+
+
+# Configurations and tasks
+| **Configuration** | **Task**                  | Description              |
+|-------------------|---------------------------|--------------------------|
+| isolet            | Multiclass classification | What letter was uttered? |
+
+# Usage
+```
+from datasets import load_dataset
+from sklearn.tree import DecisionTreeClassifier
+
+dataset = load_dataset("mstz/isolet", "isolet")["train"]
+```

isolet.py

@@ -0,0 +1,76 @@
+"""Isolet dataset."""
+
+from typing import List
+
+import datasets
+
+import pandas
+
+
+VERSION = datasets.Version("1.0.0")
+
+DESCRIPTION = "Isolet dataset from the UCI ML repository."
+_HOMEPAGE = "https://archive.ics.uci.edu/ml/datasets/Isolet"
+_URLS = ("https://archive-beta.ics.uci.edu/dataset/54/isolet")
+_CITATION = """
+@misc{misc_isolet_54,
+  author       = {Cole,Ron & Fanty,Mark},
+  title        = {{ISOLET}},
+  year         = {1994},
+  howpublished = {UCI Machine Learning Repository},
+  note         = {{DOI}: \url{10.24432/C51G69}}
+}"""
+
+# Dataset info
+urls_per_split = {
+    "train": "https://huggingface.co/datasets/mstz/isolet/raw/main/isolet1+2+3+4.data"
+}
+features_types_per_config = {
+    "isolet": {
+        str(i): datasets.Value("float64") for i in range(617)
+    }
+}
+features_types_per_config["isolet"]["618"] = datasets.ClassLabel(num_classes=26)
+features_per_config = {k: datasets.Features(features_types_per_config[k]) for k in features_types_per_config}
+
+
+class IsoletConfig(datasets.BuilderConfig):
+    def __init__(self, **kwargs):
+        super(IsoletConfig, self).__init__(version=VERSION, **kwargs)
+        self.features = features_per_config[kwargs["name"]]
+
+
+class Isolet(datasets.GeneratorBasedBuilder):
+    # dataset versions
+    DEFAULT_CONFIG = "isolet"
+    BUILDER_CONFIGS = [
+        IsoletConfig(name="isolet",
+                     description="Isolet for letter 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, config=self.config.name)
+
+        for row_id, row in data.iterrows():
+            data_row = dict(row)
+
+            yield row_id, data_row
+
+    def preprocess(self, data: pandas.DataFrame, config: str = DEFAULT_CONFIG) -> pandas.DataFrame:
+        data.columns = [str(i) for i in range(618)]
+        return data.astype({"618": "int"})

isolet1+2+3+4.data

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+version https://git-lfs.github.com/spec/v1
+oid sha256:aa935cc98ec22ee689aa5b2ddf1fdce074692f7016f0255f0982df133ccbab38
+size 32445949