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  1. .gitattributes +1 -0
  2. README.md +20 -0
  3. kddcup.data +3 -0
  4. kddcup.py +151 -0
.gitattributes CHANGED
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README.md ADDED
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+ ---
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+ language:
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+ - en
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+ tags:
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+ - kddcup
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+ - tabular_classification
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+ - binary_classification
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+ pretty_name: Kddcup
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+ task_categories: # Full list at https://github.com/huggingface/hub-docs/blob/main/js/src/lib/interfaces/Types.ts
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+ - tabular-classification
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+ configs:
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+ - kddcup
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+ ---
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+ # Kddcup
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+ The Kddcup dataset.
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+
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+ # Configurations and tasks
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+ | **Configuration** | **Task** |
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+ |-----------------------|---------------------------|
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+ | kddcup | Multiclass classification.|
kddcup.data ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:3ec2301a9a5d81b40937ba155b4713a77b60e85b89f0423257e58d566aa979fb
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+ size 742579829
kddcup.py ADDED
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+ """Kddcup Dataset"""
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+
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+ from typing import List
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+ from functools import partial
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+
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+ import datasets
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+
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+ import pandas
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+
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+
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+ VERSION = datasets.Version("1.0.0")
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+
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+ _ENCODING_DICS = {
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+ "class": {value: i
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+ for value, i in enumerate("normal.",
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+ "buffer_overflow.",
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+ "loadmodule.",
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+ "perl.",
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+ "neptune.",
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+ "smurf.",
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+ "guess_passwd.",
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+ "pod.",
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+ "teardrop.",
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+ "portsweep.",
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+ "ipsweep.",
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+ "land.",
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+ "ftp_write.",
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+ "back.",
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+ "imap.",
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+ "satan.",
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+ "phf.",
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+ "nmap.",
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+ "multihop.",
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+ "warezmaster.",
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+ "warezclient.",
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+ "spy.",
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+ "rootkit.")
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+ }
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+ }
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+
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+ DESCRIPTION = "Kddcup dataset."
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+ _HOMEPAGE = ""
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+ _URLS = ("")
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+ _CITATION = """"""
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+
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+ # Dataset info
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+ urls_per_split = {
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+ "train": "https://huggingface.co/datasets/mstz/kddcup/resolve/main/kddcup.data"
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+ }
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+ features_types_per_config = {
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+ "kddcup": {
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+ "duration": datasets.Value("float"),
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+ "protocol_type": datasets.Value("string"),
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+ "service": datasets.Value("string"),
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+ "flag": datasets.Value("string"),
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+ "src_bytes": datasets.Value("integer"),
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+ "dst_bytes": datasets.Value("integer"),
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+ "land": datasets.Value("integer"),
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+ "wrong_fragment": datasets.Value("integer"),
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+ "urgent": datasets.Value("integer"),
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+ "hot": datasets.Value("integer"),
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+ "num_failed_logins": datasets.Value("integer"),
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+ "logged_in": datasets.Value("integer"),
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+ "num_compromised": datasets.Value("integer"),
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+ "root_shell": datasets.Value("integer"),
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+ "su_attempted": datasets.Value("integer"),
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+ "num_root": datasets.Value("integer"),
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+ "num_file_creations": datasets.Value("integer"),
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+ "num_shells": datasets.Value("integer"),
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+ "num_access_files": datasets.Value("integer"),
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+ "num_outbound_cmds": datasets.Value("integer"),
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+ "is_host_login": datasets.Value("integer"),
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+ "is_guest_login": datasets.Value("integer"),
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+ "count": datasets.Value("integer"),
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+ "srv_count": datasets.Value("integer"),
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+ "serror_rate": datasets.Value("float"),
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+ "srv_serror_rate": datasets.Value("float"),
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+ "rerror_rate": datasets.Value("float"),
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+ "srv_rerror_rate": datasets.Value("float"),
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+ "same_srv_rate": datasets.Value("float"),
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+ "diff_srv_rate": datasets.Value("float"),
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+ "srv_diff_host_rate": datasets.Value("float"),
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+ "dst_host_count": datasets.Value("integer"),
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+ "dst_host_srv_count": datasets.Value("integer"),
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+ "dst_host_same_srv_rate": datasets.Value("float"),
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+ "dst_host_diff_srv_rate": datasets.Value("float"),
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+ "dst_host_same_src_port_rate": datasets.Value("float"),
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+ "dst_host_srv_diff_host_rate": datasets.Value("float"),
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+ "dst_host_serror_rate": datasets.Value("float"),
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+ "dst_host_srv_serror_rate": datasets.Value("float"),
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+ "dst_host_rerror_rate": datasets.Value("float"),
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+ "dst_host_srv_rerror_rate": datasets.Value("float"),
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+ "class": datasets.ClassLabel(num_classes=23,
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+ names=("normal.", "buffer_overflow.", "loadmodule.", "perl.", "neptune.",
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+ "smurf.", "guess_passwd.", "pod.", "teardrop.", "portsweep.",
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+ "ipsweep.", "land.", "ftp_write.", "back.", "imap.", "satan.",
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+ "phf.", "nmap.", "multihop.", "warezmaster.", "warezclient.",
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+ "spy.", "rootkit.")),
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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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+
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+
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+ class KddcupConfig(datasets.BuilderConfig):
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+ def __init__(self, **kwargs):
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+ super(KddcupConfig, self).__init__(version=VERSION, **kwargs)
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+ self.features = features_per_config[kwargs["name"]]
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+
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+
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+ class Kddcup(datasets.GeneratorBasedBuilder):
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+ # dataset versions
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+ DEFAULT_CONFIG = "kddcup"
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+ BUILDER_CONFIGS = [
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+ KddcupConfig(name="kddcup", description="Kddcup for multiclass classification.")
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+ ]
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+
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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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+
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+ return info
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+
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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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+
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+ return [
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+ datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloads["train"]}),
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+ ]
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+
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+ def _generate_examples(self, filepath: str):
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+ data = pandas.read_csv(filepath, header=None)
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+ data = self.preprocess(data)
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+
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+ for row_id, row in data.iterrows():
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+ data_row = dict(row)
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+
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+ yield row_id, data_row
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+
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+ def preprocess(self, data: pandas.DataFrame) -> pandas.DataFrame:
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+ data.columns = [f"feature_{i}" for i in range(5000)] + ["class"]
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+ for feature in _ENCODING_DICS:
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+ encoding_function = partial(self.encode, feature)
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+ data.loc[:, feature] = data[feature].apply(encoding_function)
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+
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+ return data[list(features_types_per_config[self.config.name].keys())]
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+
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+ def encode(self, feature, value):
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+ if feature in _ENCODING_DICS:
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+ return _ENCODING_DICS[feature][value]
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+ raise ValueError(f"Unknown feature: {feature}")