Datasets:
File size: 2,507 Bytes
5804590 c0f929b 5804590 99afcff 5804590 252362a 5804590 0dda3db 5804590 7257267 5804590 252362a |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 |
"""Isolet dataset."""
from typing import List
import datasets
import pandas
VERSION = datasets.Version("1.0.0")
DESCRIPTION = "Isolet dataset from the UCI ML repository."
_HOMEPAGE = "https://archive.ics.uci.edu/ml/datasets/Isolet"
_URLS = ("https://archive-beta.ics.uci.edu/dataset/54/isolet")
_CITATION = """
@misc{misc_isolet_54,
author = {Cole,Ron & Fanty,Mark},
title = {{ISOLET}},
year = {1994},
howpublished = {UCI Machine Learning Repository},
note = {{DOI}: \\url{10.24432/C51G69}}
}"""
# Dataset info
urls_per_split = {
"train": "https://github.com/riccotti/InterpretableModels/raw/master/datasets/isolet.data.gz"
}
features_types_per_config = {
"isolet": {
str(i): datasets.Value("float64") for i in range(617)
}
}
features_types_per_config["isolet"]["617"] = datasets.ClassLabel(num_classes=26)
features_per_config = {k: datasets.Features(features_types_per_config[k]) for k in features_types_per_config}
class IsoletConfig(datasets.BuilderConfig):
def __init__(self, **kwargs):
super(IsoletConfig, self).__init__(version=VERSION, **kwargs)
self.features = features_per_config[kwargs["name"]]
class Isolet(datasets.GeneratorBasedBuilder):
# dataset versions
DEFAULT_CONFIG = "isolet"
BUILDER_CONFIGS = [
IsoletConfig(name="isolet",
description="Isolet for letter 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"]})
]
def _generate_examples(self, filepath: str):
data = pandas.read_csv(filepath, header=None)
data = self.preprocess(data, config=self.config.name)
for row_id, row in data.iterrows():
data_row = dict(row)
yield row_id, data_row
def preprocess(self, data: pandas.DataFrame, config: str = DEFAULT_CONFIG) -> pandas.DataFrame:
print(data.shape)
print(data.columns)
data.columns = [str(i) for i in range(618)]
return data.astype({"617": "int"})
|