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Datasets:
mstz
/
musk

Tasks:
Tabular Classification
Modalities:
Tabular
Languages:
English
Size:
< 1K
Tags:
musk
tabular_classification
binary_classification
multiclass_classification
UCI
Libraries:
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License:
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musk
File size: 9,689 Bytes 
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"""Musk: A Census Dataset"""

from typing import List
from functools import partial

import datasets

import pandas


VERSION = datasets.Version("1.0.0")
_BASE_FEATURE_NAMES = [
    "name",
    "conformation_name",
    "ray_0",
    "ray_1",
    "ray_2",
    "ray_3",
    "ray_4",
    "ray_5",
    "ray_6",
    "ray_7",
    "ray_8",
    "ray_9",
    "ray_10",
    "ray_11",
    "ray_12",
    "ray_13",
    "ray_14",
    "ray_15",
    "ray_16",
    "ray_17",
    "ray_18",
    "ray_19",
    "ray_20",
    "ray_21",
    "ray_22",
    "ray_23",
    "ray_24",
    "ray_25",
    "ray_26",
    "ray_27",
    "ray_28",
    "ray_29",
    "ray_30",
    "ray_31",
    "ray_32",
    "ray_33",
    "ray_34",
    "ray_35",
    "ray_36",
    "ray_37",
    "ray_38",
    "ray_39",
    "ray_40",
    "ray_41",
    "ray_42",
    "ray_43",
    "ray_44",
    "ray_45",
    "ray_46",
    "ray_47",
    "ray_48",
    "ray_49",
    "ray_50",
    "ray_51",
    "ray_52",
    "ray_53",
    "ray_54",
    "ray_55",
    "ray_56",
    "ray_57",
    "ray_58",
    "ray_59",
    "ray_60",
    "ray_61",
    "oxy_distance",
    "displacement_1",
    "displacement_2",
    "displacement_3",
    "is_musk"
]

DESCRIPTION = "Musk dataset from the UCI ML repository."
_HOMEPAGE = "https://archive.ics.uci.edu/ml/datasets/Musk"
_URLS = ("https://huggingface.co/datasets/mstz/musk/raw/musk.csv")
_CITATION = """
@misc{misc_musk_(version_1)_74,
  author       = {Chapman,David & Jain,Ajay},
  title        = {{Musk (Version 1)}},
  year         = {1994},
  howpublished = {UCI Machine Learning Repository},
  note         = {{DOI}: \\url{10.24432/C5ZK5B}}
}"""

# Dataset info
urls_per_split = {
    "musk1": {
        "train": "https://huggingface.co/datasets/mstz/musk/raw/main/clean1.data"
    },
    "musk2": {
        "train": "https://huggingface.co/datasets/mstz/musk/raw/main/clean2.data"
    }
}
features_types_per_config = {
    "musk1": {
        "ray_0": datasets.Value("float64"),
        "ray_1": datasets.Value("float64"),
        "ray_2": datasets.Value("float64"),
        "ray_3": datasets.Value("float64"),
        "ray_4": datasets.Value("float64"),
        "ray_5": datasets.Value("float64"),
        "ray_6": datasets.Value("float64"),
        "ray_7": datasets.Value("float64"),
        "ray_8": datasets.Value("float64"),
        "ray_9": datasets.Value("float64"),
        "ray_10": datasets.Value("float64"),
        "ray_11": datasets.Value("float64"),
        "ray_12": datasets.Value("float64"),
        "ray_13": datasets.Value("float64"),
        "ray_14": datasets.Value("float64"),
        "ray_15": datasets.Value("float64"),
        "ray_16": datasets.Value("float64"),
        "ray_17": datasets.Value("float64"),
        "ray_18": datasets.Value("float64"),
        "ray_19": datasets.Value("float64"),
        "ray_20": datasets.Value("float64"),
        "ray_21": datasets.Value("float64"),
        "ray_22": datasets.Value("float64"),
        "ray_23": datasets.Value("float64"),
        "ray_24": datasets.Value("float64"),
        "ray_25": datasets.Value("float64"),
        "ray_26": datasets.Value("float64"),
        "ray_27": datasets.Value("float64"),
        "ray_28": datasets.Value("float64"),
        "ray_29": datasets.Value("float64"),
        "ray_30": datasets.Value("float64"),
        "ray_31": datasets.Value("float64"),
        "ray_32": datasets.Value("float64"),
        "ray_33": datasets.Value("float64"),
        "ray_34": datasets.Value("float64"),
        "ray_35": datasets.Value("float64"),
        "ray_36": datasets.Value("float64"),
        "ray_37": datasets.Value("float64"),
        "ray_38": datasets.Value("float64"),
        "ray_39": datasets.Value("float64"),
        "ray_40": datasets.Value("float64"),
        "ray_41": datasets.Value("float64"),
        "ray_42": datasets.Value("float64"),
        "ray_43": datasets.Value("float64"),
        "ray_44": datasets.Value("float64"),
        "ray_45": datasets.Value("float64"),
        "ray_46": datasets.Value("float64"),
        "ray_47": datasets.Value("float64"),
        "ray_48": datasets.Value("float64"),
        "ray_49": datasets.Value("float64"),
        "ray_50": datasets.Value("float64"),
        "ray_51": datasets.Value("float64"),
        "ray_52": datasets.Value("float64"),
        "ray_53": datasets.Value("float64"),
        "ray_54": datasets.Value("float64"),
        "ray_55": datasets.Value("float64"),
        "ray_56": datasets.Value("float64"),
        "ray_57": datasets.Value("float64"),
        "ray_58": datasets.Value("float64"),
        "ray_59": datasets.Value("float64"),
        "ray_60": datasets.Value("float64"),
        "ray_61": datasets.Value("float64"),
        "oxy_distance": datasets.Value("float64"),
        "displacement_1": datasets.Value("float64"),
        "displacement_2": datasets.Value("float64"),
        "displacement_3": datasets.Value("float64"),
        "is_musk": datasets.ClassLabel(num_classes=2, names=("no", "yes"))
    },
    "musk2": {
        "ray_0": datasets.Value("float64"),
        "ray_1": datasets.Value("float64"),
        "ray_2": datasets.Value("float64"),
        "ray_3": datasets.Value("float64"),
        "ray_4": datasets.Value("float64"),
        "ray_5": datasets.Value("float64"),
        "ray_6": datasets.Value("float64"),
        "ray_7": datasets.Value("float64"),
        "ray_8": datasets.Value("float64"),
        "ray_9": datasets.Value("float64"),
        "ray_10": datasets.Value("float64"),
        "ray_11": datasets.Value("float64"),
        "ray_12": datasets.Value("float64"),
        "ray_13": datasets.Value("float64"),
        "ray_14": datasets.Value("float64"),
        "ray_15": datasets.Value("float64"),
        "ray_16": datasets.Value("float64"),
        "ray_17": datasets.Value("float64"),
        "ray_18": datasets.Value("float64"),
        "ray_19": datasets.Value("float64"),
        "ray_20": datasets.Value("float64"),
        "ray_21": datasets.Value("float64"),
        "ray_22": datasets.Value("float64"),
        "ray_23": datasets.Value("float64"),
        "ray_24": datasets.Value("float64"),
        "ray_25": datasets.Value("float64"),
        "ray_26": datasets.Value("float64"),
        "ray_27": datasets.Value("float64"),
        "ray_28": datasets.Value("float64"),
        "ray_29": datasets.Value("float64"),
        "ray_30": datasets.Value("float64"),
        "ray_31": datasets.Value("float64"),
        "ray_32": datasets.Value("float64"),
        "ray_33": datasets.Value("float64"),
        "ray_34": datasets.Value("float64"),
        "ray_35": datasets.Value("float64"),
        "ray_36": datasets.Value("float64"),
        "ray_37": datasets.Value("float64"),
        "ray_38": datasets.Value("float64"),
        "ray_39": datasets.Value("float64"),
        "ray_40": datasets.Value("float64"),
        "ray_41": datasets.Value("float64"),
        "ray_42": datasets.Value("float64"),
        "ray_43": datasets.Value("float64"),
        "ray_44": datasets.Value("float64"),
        "ray_45": datasets.Value("float64"),
        "ray_46": datasets.Value("float64"),
        "ray_47": datasets.Value("float64"),
        "ray_48": datasets.Value("float64"),
        "ray_49": datasets.Value("float64"),
        "ray_50": datasets.Value("float64"),
        "ray_51": datasets.Value("float64"),
        "ray_52": datasets.Value("float64"),
        "ray_53": datasets.Value("float64"),
        "ray_54": datasets.Value("float64"),
        "ray_55": datasets.Value("float64"),
        "ray_56": datasets.Value("float64"),
        "ray_57": datasets.Value("float64"),
        "ray_58": datasets.Value("float64"),
        "ray_59": datasets.Value("float64"),
        "ray_60": datasets.Value("float64"),
        "ray_61": datasets.Value("float64"),
        "oxy_distance": datasets.Value("float64"),
        "displacement_1": datasets.Value("float64"),
        "displacement_2": datasets.Value("float64"),
        "displacement_3": datasets.Value("float64"),
        "is_musk": 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 MuskConfig(datasets.BuilderConfig):
    def __init__(self, **kwargs):
        super(MuskConfig, self).__init__(version=VERSION, **kwargs)
        self.features = features_per_config[kwargs["name"]]


class Musk(datasets.GeneratorBasedBuilder):
    # dataset versions
    DEFAULT_CONFIG = "musk1"
    BUILDER_CONFIGS = [
        MuskConfig(name="musk1",
                    description="Musk for binary classification."),
        MuskConfig(name="musk2",
                    description="Musk 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[self.config.name]["train"]})
        ]
    
    def _generate_examples(self, filepath: str):
        data = pandas.read_csv(filepath, header=None)
        data.columns = _BASE_FEATURE_NAMES
        data = data.drop("name", axis="columns", inplace=True)
        data = data.drop("conformation_name", axis="columns", inplace=True)

        for row_id, row in data.iterrows():
            data_row = dict(row)

            yield row_id, data_row