| """Soybean Dataset""" |
|
|
| from typing import List |
| from functools import partial |
|
|
| import datasets |
|
|
| import pandas |
|
|
|
|
| VERSION = datasets.Version("1.0.0") |
|
|
| _ENCODING_DICS = { |
| "class": { |
| value: i for i, value in enumerate(["diaporthe_stem_canker", |
| "charcoal_rot", "rhizoctonia_root_rot", |
| "phytophthora_rot", "brown_stem_rot", "powdery_mildew", |
| "downy_mildew", "brown_spot", "bacterial_blight", |
| "bacterial_pustule", "purple_seed_stain", "anthracnose", |
| "phyllosticta_leaf_spot", "alternarialeaf_spot", |
| "frog_eye_leaf_spot", "diaporthe_pod_&_stem_blight", |
| "cyst_nematode", "2_4_d_injury", "herbicide_injury"]) |
| } |
| } |
| _BASE_FEATURE_NAMES = [ |
| "date", |
| "plant_stand", |
| "precip", |
| "temp", |
| "hail", |
| "crop_hist", |
| "area_damaged", |
| "severity", |
| "seed_tmt", |
| "germination", |
| "plant_growth", |
| "leaves", |
| "leafspots_halo", |
| "leafspots_marg", |
| "leafspot_size", |
| "leaf_shread", |
| "leaf_malf", |
| "leaf_mild", |
| "stem", |
| "lodging", |
| "stem_cankers", |
| "canker_lesion", |
| "fruiting_bodies", |
| "external decay", |
| "mycelium", |
| "int_discolor", |
| "sclerotia", |
| "fruit_pods", |
| "fruit spots", |
| "seed", |
| "mold_growth", |
| "seed_discolor", |
| "seed_size", |
| "shriveling", |
| "roots", |
| "class", |
| ] |
|
|
| DESCRIPTION = "Soybean dataset." |
| _HOMEPAGE = "https://archive-beta.ics.uci.edu/dataset/116/us+census+data+1990" |
| _URLS = ("https://archive-beta.ics.uci.edu/dataset/116/us+census+data+1990") |
| _CITATION = """ |
| @misc{misc_soybean_(large)_90, |
| author = {Michalski,R.S. & Chilausky,R.L.}, |
| title = {{Soybean (Large)}}, |
| year = {1988}, |
| howpublished = {UCI Machine Learning Repository}, |
| note = {{DOI}: \\url{10.24432/C5JG6Z}} |
| } |
| """ |
|
|
| |
| urls_per_split = { |
| "train": "https://huggingface.co/datasets/mstz/soybean/resolve/main/soybean.csv" |
| } |
| features_types_per_config = { |
| "soybean": { |
| "date": datasets.Value("string"), |
| "plant_stand": datasets.Value("string"), |
| "precip": datasets.Value("string"), |
| "temp": datasets.Value("string"), |
| "hail": datasets.Value("string"), |
| "crop_hist": datasets.Value("string"), |
| "area_damaged": datasets.Value("string"), |
| "severity": datasets.Value("string"), |
| "seed_tmt": datasets.Value("string"), |
| "germination": datasets.Value("string"), |
| "plant_growth": datasets.Value("string"), |
| "leaves": datasets.Value("string"), |
| "leafspots_halo": datasets.Value("string"), |
| "leafspots_marg": datasets.Value("string"), |
| "leafspot_size": datasets.Value("string"), |
| "leaf_shread": datasets.Value("string"), |
| "leaf_malf": datasets.Value("string"), |
| "leaf_mild": datasets.Value("string"), |
| "stem": datasets.Value("string"), |
| "lodging": datasets.Value("string"), |
| "stem_cankers": datasets.Value("string"), |
| "canker_lesion": datasets.Value("string"), |
| "fruiting_bodies": datasets.Value("string"), |
| "external decay": datasets.Value("string"), |
| "mycelium": datasets.Value("string"), |
| "int_discolor": datasets.Value("string"), |
| "sclerotia": datasets.Value("string"), |
| "fruit_pods": datasets.Value("string"), |
| "fruit spots": datasets.Value("string"), |
| "seed": datasets.Value("string"), |
| "mold_growth": datasets.Value("string"), |
| "seed_discolor": datasets.Value("string"), |
| "seed_size": datasets.Value("string"), |
| "shriveling": datasets.Value("string"), |
| "roots": datasets.Value("string"), |
| "class": datasets.ClassLabel(num_classes=19, |
| names=["diaporthe_stem_canker", |
| "charcoal_rot", "rhizoctonia_root_rot", |
| "phytophthora_rot", "brown_stem_rot", "powdery_mildew", |
| "downy_mildew", "brown_spot", "bacterial_blight", |
| "bacterial_pustule", "purple_seed_stain", "anthracnose", |
| "phyllosticta_leaf_spot", "alternarialeaf_spot", |
| "frog_eye_leaf_spot", "diaporthe_pod_&_stem_blight", |
| "cyst_nematode", "2_4_d_injury", "herbicide_injury"]) |
| } |
| } |
| for c in _ENCODING_DICS["class"].keys(): |
| features_types_per_config[c] = { |
| "date": datasets.Value("string"), |
| "plant_stand": datasets.Value("string"), |
| "precip": datasets.Value("string"), |
| "temp": datasets.Value("string"), |
| "hail": datasets.Value("string"), |
| "crop_hist": datasets.Value("string"), |
| "area_damaged": datasets.Value("string"), |
| "severity": datasets.Value("string"), |
| "seed_tmt": datasets.Value("string"), |
| "germination": datasets.Value("string"), |
| "plant_growth": datasets.Value("string"), |
| "leaves": datasets.Value("string"), |
| "leafspots_halo": datasets.Value("string"), |
| "leafspots_marg": datasets.Value("string"), |
| "leafspot_size": datasets.Value("string"), |
| "leaf_shread": datasets.Value("string"), |
| "leaf_malf": datasets.Value("string"), |
| "leaf_mild": datasets.Value("string"), |
| "stem": datasets.Value("string"), |
| "lodging": datasets.Value("string"), |
| "stem_cankers": datasets.Value("string"), |
| "canker_lesion": datasets.Value("string"), |
| "fruiting_bodies": datasets.Value("string"), |
| "external decay": datasets.Value("string"), |
| "mycelium": datasets.Value("string"), |
| "int_discolor": datasets.Value("string"), |
| "sclerotia": datasets.Value("string"), |
| "fruit_pods": datasets.Value("string"), |
| "fruit spots": datasets.Value("string"), |
| "seed": datasets.Value("string"), |
| "mold_growth": datasets.Value("string"), |
| "seed_discolor": datasets.Value("string"), |
| "seed_size": datasets.Value("string"), |
| "shriveling": datasets.Value("string"), |
| "roots": datasets.Value("string"), |
| "class": datasets.ClassLabel(num_classes=2, names=("no", "yes")) |
| } |
|
|
| features_per_config = {k: datasets.Features(features_types_per_config[k]) for k in features_types_per_config} |
|
|
|
|
| class SoybeanConfig(datasets.BuilderConfig): |
| def __init__(self, **kwargs): |
| super(SoybeanConfig, self).__init__(version=VERSION, **kwargs) |
| self.features = features_per_config[kwargs["name"]] |
|
|
|
|
| class Soybean(datasets.GeneratorBasedBuilder): |
| |
| DEFAULT_CONFIG = "soybean" |
| binary_configurations = [SoybeanConfig(name=c, description=f"Is this instance of class {c}?") |
| for c in _ENCODING_DICS["class"].keys()] |
| BUILDER_CONFIGS = [SoybeanConfig(name="soybean", description="Soybean for binary classification.")] |
| BUILDER_CONFIGS += binary_configurations |
|
|
|
|
| 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: |
| data.columns = _BASE_FEATURE_NAMES |
| data["class"] = data["class"].apply(lambda x: x.replace("-", "_")) |
|
|
| for c in _ENCODING_DICS["class"].keys(): |
| if self.config.name == c: |
| data["class"] = data["class"].apply(lambda x: 1 if x == c else 0) |
| break |
|
|
| for feature in _ENCODING_DICS: |
| encoding_function = partial(self.encode, feature) |
| data[feature] = data[feature].apply(encoding_function) |
| |
| data = data.rename(columns={"instance migration_code_change_in_msa": "migration_code_change_in_msa"}) |
|
|
| |
| 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}") |
|
|
