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from typing import List |
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import datasets |
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import pandas |
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import gzip |
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VERSION = datasets.Version("1.0.0") |
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DESCRIPTION = "Covertype dataset from the UCI ML repository." |
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_HOMEPAGE = "https://archive-beta.ics.uci.edu/dataset/31/covertype" |
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_URLS = ("https://archive-beta.ics.uci.edu/dataset/31/covertype") |
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_CITATION = """""" |
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urls_per_split = { |
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"train": "https://archive.ics.uci.edu/ml/machine-learning-databases/covtype/covtype.data.gz" |
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} |
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_BASE_FEATURE_NAMES = [ |
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"elevation", |
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"aspect", |
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"slope", |
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"horizontal_distance_to_hydrology", |
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"vertical_distance_to_hydrology", |
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"horizontal_distance_to_roadways", |
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"hillshade_9am", |
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"hillshade_noon", |
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"hillshade_3pm", |
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"horizontal_distance_to_fire_points", |
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"wilderness_area_id_0", |
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"wilderness_area_id_1", |
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"wilderness_area_id_2", |
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"wilderness_area_id_3", |
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"soil_type_id_0", |
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"soil_type_id_1", |
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"soil_type_id_2", |
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"soil_type_id_3", |
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"soil_type_id_4", |
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"soil_type_id_5", |
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"soil_type_id_6", |
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"soil_type_id_7", |
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"soil_type_id_8", |
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"soil_type_id_9", |
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"soil_type_id_10", |
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"soil_type_id_11", |
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"soil_type_id_12", |
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"soil_type_id_13", |
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"soil_type_id_14", |
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"soil_type_id_15", |
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"soil_type_id_16", |
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"soil_type_id_17", |
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"soil_type_id_18", |
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"soil_type_id_19", |
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"soil_type_id_20", |
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"soil_type_id_21", |
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"soil_type_id_22", |
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"soil_type_id_23", |
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"soil_type_id_24", |
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"soil_type_id_25", |
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"soil_type_id_26", |
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"soil_type_id_27", |
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"soil_type_id_28", |
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"soil_type_id_29", |
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"soil_type_id_30", |
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"soil_type_id_31", |
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"soil_type_id_32", |
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"soil_type_id_33", |
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"soil_type_id_34", |
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"soil_type_id_35", |
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"soil_type_id_36", |
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"soil_type_id_37", |
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"soil_type_id_38", |
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"soil_type_id_39", |
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"cover_type" |
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] |
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features_types_per_config = { |
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"covertype": { |
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"elevation": datasets.Value("float32"), |
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"aspect": datasets.Value("float32"), |
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"slope": datasets.Value("float32"), |
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"horizontal_distance_to_hydrology": datasets.Value("float32"), |
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"vertical_distance_to_hydrology": datasets.Value("float32"), |
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"horizontal_distance_to_roadways": datasets.Value("float32"), |
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"hillshade_9am": datasets.Value("float32"), |
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"hillshade_noon": datasets.Value("float32"), |
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"hillshade_3pm": datasets.Value("float32"), |
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"horizontal_distance_to_fire_points": datasets.Value("float32"), |
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"wilderness_area_id_0": datasets.Value("bool"), |
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"wilderness_area_id_1": datasets.Value("bool"), |
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"wilderness_area_id_2": datasets.Value("bool"), |
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"wilderness_area_id_3": datasets.Value("bool"), |
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"soil_type_id_0": datasets.Value("bool"), |
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"soil_type_id_1": datasets.Value("bool"), |
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"soil_type_id_2": datasets.Value("bool"), |
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"soil_type_id_3": datasets.Value("bool"), |
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"soil_type_id_4": datasets.Value("bool"), |
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"soil_type_id_5": datasets.Value("bool"), |
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"soil_type_id_6": datasets.Value("bool"), |
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"soil_type_id_7": datasets.Value("bool"), |
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"soil_type_id_8": datasets.Value("bool"), |
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"soil_type_id_9": datasets.Value("bool"), |
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"soil_type_id_10": datasets.Value("bool"), |
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"soil_type_id_11": datasets.Value("bool"), |
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"soil_type_id_12": datasets.Value("bool"), |
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"soil_type_id_13": datasets.Value("bool"), |
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"soil_type_id_14": datasets.Value("bool"), |
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"soil_type_id_15": datasets.Value("bool"), |
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"soil_type_id_16": datasets.Value("bool"), |
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"soil_type_id_17": datasets.Value("bool"), |
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"soil_type_id_18": datasets.Value("bool"), |
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"soil_type_id_19": datasets.Value("bool"), |
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"soil_type_id_20": datasets.Value("bool"), |
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"soil_type_id_21": datasets.Value("bool"), |
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"soil_type_id_22": datasets.Value("bool"), |
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"soil_type_id_23": datasets.Value("bool"), |
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"soil_type_id_24": datasets.Value("bool"), |
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"soil_type_id_25": datasets.Value("bool"), |
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"soil_type_id_26": datasets.Value("bool"), |
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"soil_type_id_27": datasets.Value("bool"), |
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"soil_type_id_28": datasets.Value("bool"), |
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"soil_type_id_29": datasets.Value("bool"), |
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"soil_type_id_30": datasets.Value("bool"), |
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"soil_type_id_31": datasets.Value("bool"), |
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"soil_type_id_32": datasets.Value("bool"), |
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"soil_type_id_33": datasets.Value("bool"), |
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"soil_type_id_34": datasets.Value("bool"), |
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"soil_type_id_35": datasets.Value("bool"), |
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"soil_type_id_36": datasets.Value("bool"), |
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"soil_type_id_37": datasets.Value("bool"), |
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"soil_type_id_38": datasets.Value("bool"), |
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"soil_type_id_39": datasets.Value("bool"), |
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"soil_type": datasets.Value("string"), |
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"cover_type": datasets.ClassLabel(num_classes=7) |
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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 CovertypeConfig(datasets.BuilderConfig): |
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def __init__(self", |
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" **kwargs): |
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super(CovertypeConfig", |
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" self).__init__(version=VERSION", |
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" **kwargs) |
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self.features = features_per_config[kwargs["name"]] |
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class Covertype(datasets.GeneratorBasedBuilder): |
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DEFAULT_CONFIG = "covertype" |
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BUILDER_CONFIGS = [ |
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CovertypeConfig(name="covertype"", |
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description="Covertype for multiclass classification.") |
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] |
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def _info(self): |
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if self.config.name not in features_per_config: |
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raise ValueError(f"Unknown configuration: {self.config.name}") |
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info = datasets.DatasetInfo(description=DESCRIPTION", |
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" citation=_CITATION", |
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" 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", |
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" 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", |
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" gen_kwargs={"filepath": downloads["train"]}) |
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] |
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def _generate_examples(self", |
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" filepath: str): |
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" header=None) |
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# except gzip.BadGzipFile: |
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data = pandas.read_csv(filepath", |
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" header=None) |
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print(data.columns) |
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print(data.shape[1]", |
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" len(_BASE_FEATURE_NAMES)) |
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data.columns = _BASE_FEATURE_NAMES |
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data = self.preprocess(data", |
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" config=self.config.name) |
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for row_id", |
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" row in data.iterrows(): |
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data_row = dict(row) |
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yield row_id", |
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" data_row |
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def preprocess(self", |
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" data: pandas.DataFrame", |
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" config: str = DEFAULT_CONFIG) -> pandas.DataFrame: |
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data.loc[:", |
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" "cover_type"] = data["cover_type"].apply(lambda x: x - 1) |
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return data |
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