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README.md

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 ---
-license: cc-by-4.0
+language:
+- en
+tags:
+- hill
+- tabular_classification
+- binary_classification
+pretty_name: Hill
+size_categories:
+- 100<n<1K
+task_categories:  # Full list at https://github.com/huggingface/hub-docs/blob/main/js/src/lib/interfaces/Types.ts
+- tabular-classification
+configs:
+- hill
+
 ---
+# Hill
+The [Hill dataset](https://archive.ics.uci.edu/ml/datasets/Hill) from the [UCI ML repository](https://archive.ics.uci.edu/ml/datasets).
+Do the plotted coordinates draw a hill?
+
+# Configurations and tasks
+| **Configuration** | **Task**                  | **Description**                          |
+|-------------------|---------------------------|------------------------------------------|
+| hill              | Binary classification     | Do the plotted coordinates draw a hill?  |
+
+# Usage
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("mstz/hill", "hill")["train"]
+```
+
+# Features
+Features are the coordinates of the drawn point. Feature `X{i}` is the `y` coordinate of the point `(i, X{i})`.

hill.py

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+"""Hill"""
+
+from typing import List
+
+import datasets
+
+import pandas
+
+
+VERSION = datasets.Version("1.0.0")
+
+DESCRIPTION = "Hill dataset from the UCI ML repository."
+_HOMEPAGE = "https://archive.ics.uci.edu/ml/datasets/Hill"
+_URLS = ("https://archive.ics.uci.edu/ml/datasets/Hill")
+_CITATION = """
+@misc{misc_hill-valley_166,
+  author       = {Graham,Lee & Oppacher,Franz},
+  title        = {{Hill-Valley}},
+  year         = {2008},
+  howpublished = {UCI Machine Learning Repository},
+  note         = {{DOI}: \\url{10.24432/C5JC8P}}
+}"""
+
+# Dataset info
+urls_per_split = {
+    "train": "Hill_Valley_without_noise_Training.data", 
+    "test": "Hill_Valley_without_noise_Testing.data"
+}
+features_types_per_config = {
+    "hill": {
+        "X1": datasets.Value("float64"),
+        "X2": datasets.Value("float64"),
+        "X3": datasets.Value("float64"),
+        "X4": datasets.Value("float64"),
+        "X5": datasets.Value("float64"),
+        "X6": datasets.Value("float64"),
+        "X7": datasets.Value("float64"),
+        "X8": datasets.Value("float64"),
+        "X9": datasets.Value("float64"),
+        "X10": datasets.Value("float64"),
+        "X11": datasets.Value("float64"),
+        "X12": datasets.Value("float64"),
+        "X13": datasets.Value("float64"),
+        "X14": datasets.Value("float64"),
+        "X15": datasets.Value("float64"),
+        "X16": datasets.Value("float64"),
+        "X17": datasets.Value("float64"),
+        "X18": datasets.Value("float64"),
+        "X19": datasets.Value("float64"),
+        "X20": datasets.Value("float64"),
+        "X21": datasets.Value("float64"),
+        "X22": datasets.Value("float64"),
+        "X23": datasets.Value("float64"),
+        "X24": datasets.Value("float64"),
+        "X25": datasets.Value("float64"),
+        "X26": datasets.Value("float64"),
+        "X27": datasets.Value("float64"),
+        "X28": datasets.Value("float64"),
+        "X29": datasets.Value("float64"),
+        "X30": datasets.Value("float64"),
+        "X31": datasets.Value("float64"),
+        "X32": datasets.Value("float64"),
+        "X33": datasets.Value("float64"),
+        "X34": datasets.Value("float64"),
+        "X35": datasets.Value("float64"),
+        "X36": datasets.Value("float64"),
+        "X37": datasets.Value("float64"),
+        "X38": datasets.Value("float64"),
+        "X39": datasets.Value("float64"),
+        "X40": datasets.Value("float64"),
+        "X41": datasets.Value("float64"),
+        "X42": datasets.Value("float64"),
+        "X43": datasets.Value("float64"),
+        "X44": datasets.Value("float64"),
+        "X45": datasets.Value("float64"),
+        "X46": datasets.Value("float64"),
+        "X47": datasets.Value("float64"),
+        "X48": datasets.Value("float64"),
+        "X49": datasets.Value("float64"),
+        "X50": datasets.Value("float64"),
+        "X51": datasets.Value("float64"),
+        "X52": datasets.Value("float64"),
+        "X53": datasets.Value("float64"),
+        "X54": datasets.Value("float64"),
+        "X55": datasets.Value("float64"),
+        "X56": datasets.Value("float64"),
+        "X57": datasets.Value("float64"),
+        "X58": datasets.Value("float64"),
+        "X59": datasets.Value("float64"),
+        "X60": datasets.Value("float64"),
+        "X61": datasets.Value("float64"),
+        "X62": datasets.Value("float64"),
+        "X63": datasets.Value("float64"),
+        "X64": datasets.Value("float64"),
+        "X65": datasets.Value("float64"),
+        "X66": datasets.Value("float64"),
+        "X67": datasets.Value("float64"),
+        "X68": datasets.Value("float64"),
+        "X69": datasets.Value("float64"),
+        "X70": datasets.Value("float64"),
+        "X71": datasets.Value("float64"),
+        "X72": datasets.Value("float64"),
+        "X73": datasets.Value("float64"),
+        "X74": datasets.Value("float64"),
+        "X75": datasets.Value("float64"),
+        "X76": datasets.Value("float64"),
+        "X77": datasets.Value("float64"),
+        "X78": datasets.Value("float64"),
+        "X79": datasets.Value("float64"),
+        "X80": datasets.Value("float64"),
+        "X81": datasets.Value("float64"),
+        "X82": datasets.Value("float64"),
+        "X83": datasets.Value("float64"),
+        "X84": datasets.Value("float64"),
+        "X85": datasets.Value("float64"),
+        "X86": datasets.Value("float64"),
+        "X87": datasets.Value("float64"),
+        "X88": datasets.Value("float64"),
+        "X89": datasets.Value("float64"),
+        "X90": datasets.Value("float64"),
+        "X91": datasets.Value("float64"),
+        "X92": datasets.Value("float64"),
+        "X93": datasets.Value("float64"),
+        "X94": datasets.Value("float64"),
+        "X95": datasets.Value("float64"),
+        "X96": datasets.Value("float64"),
+        "X97": datasets.Value("float64"),
+        "X98": datasets.Value("float64"),
+        "X99": datasets.Value("float64"),
+        "X100": datasets.Value("float64"),
+        "class": datasets.ClassLabel(num_classes=2)
+    }
+}
+features_per_config = {k: datasets.Features(features_types_per_config[k]) for k in features_types_per_config}
+
+
+class HillConfig(datasets.BuilderConfig):
+    def __init__(self, **kwargs):
+        super(HillConfig, self).__init__(version=VERSION, **kwargs)
+        self.features = features_per_config[kwargs["name"]]
+
+
+class Hill(datasets.GeneratorBasedBuilder):
+    # dataset versions
+    DEFAULT_CONFIG = "hill"
+    BUILDER_CONFIGS = [
+        HillConfig(name="hill",
+                    description="Hill for binary 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"]}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloads["test"]}),
+        ]
+    
+    def _generate_examples(self, filepath: str):
+        data = pandas.read_csv(filepath)
+ 
+        for row_id, row in data.iterrows():
+            data_row = dict(row)
+
+            yield row_id, data_row