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