0Ph6dZddlZddlZddlZddlmZddlmZmZddl m Z m Z ddl Z ddl ZddlmZmZddlmZdd lmZmZmZd d lmZd d lmZmZmZmZed ddZedddZ ej!e"Z#eehddge$ej%dgdgdgdgdgdgdgeed ddgeedddgd ddddddddddd d d!Z& d$d"Z'd#Z(dS)%zKDDCUP 99 dataset. A classic dataset for anomaly detection. The dataset page is available from UCI Machine Learning Repository https://archive.ics.uci.edu/ml/machine-learning-databases/kddcup99-mld/kddcup.data.gz N)GzipFile)IntegralReal)existsjoin)Bunchcheck_random_state)shuffle)Interval StrOptionsvalidate_params) get_data_home)RemoteFileMetadata_convert_data_dataframe _fetch_remote load_descr kddcup99_dataz.https://ndownloader.figshare.com/files/5976045@3b6c942aa0356c0ca35b7b595a26c89d343652c9db428893e7494f837b274292)filenameurlchecksumkddcup99_10_dataz.https://ndownloader.figshare.com/files/5976042@8045aca0d84e70e622d1148d7df782496f6333bf6eb979a1b0837c42a9fd9561>SASFhttpsmtpboolean random_stateleft)closedgneither) subset data_homer r! percent10download_if_missing return_X_yas_frame n_retriesdelayT)prefer_skip_nested_validationF?c t|}t||||| } | j} | j} | j} | j}|dkr| dk}t j|}| |ddf}| |}| |ddf}| |}|jd}t|}| d|d}||}||}t j ||f} t j ||f} |dks |d ks|d kr]| ddd fd k}t j | |dd f| |d dff} | dd | d dz} | |} t j | dddfdztd| dddf<t j | dddfdztd| dddf<t j | dddfdztd| dddf<|d krj| dddfdk}| |} | |} t j | dddf| dddf| dddff} | d| d| dg} |d krj| dddfdk}| |} | |} t j | dddf| dddf| dddff} | d| d| dg} |dkr\t j | dddf| dddf| dddf| dddff} | d| d| d| dg} |rt!| | |\} } t#d}d}|rt%d| | | |\}} } |r| | fSt'| | ||| |S)a Load the kddcup99 dataset (classification). Download it if necessary. ================= ==================================== Classes 23 Samples total 4898431 Dimensionality 41 Features discrete (int) or continuous (float) ================= ==================================== Read more in the :ref:`User Guide `. .. versionadded:: 0.18 Parameters ---------- subset : {'SA', 'SF', 'http', 'smtp'}, default=None To return the corresponding classical subsets of kddcup 99. If None, return the entire kddcup 99 dataset. data_home : str or path-like, default=None Specify another download and cache folder for the datasets. By default all scikit-learn data is stored in '~/scikit_learn_data' subfolders. .. versionadded:: 0.19 shuffle : bool, default=False Whether to shuffle dataset. random_state : int, RandomState instance or None, default=None Determines random number generation for dataset shuffling and for selection of abnormal samples if `subset='SA'`. Pass an int for reproducible output across multiple function calls. See :term:`Glossary `. percent10 : bool, default=True Whether to load only 10 percent of the data. download_if_missing : bool, default=True If False, raise an OSError if the data is not locally available instead of trying to download the data from the source site. return_X_y : bool, default=False If True, returns ``(data, target)`` instead of a Bunch object. See below for more information about the `data` and `target` object. .. versionadded:: 0.20 as_frame : bool, default=False If `True`, returns a pandas Dataframe for the ``data`` and ``target`` objects in the `Bunch` returned object; `Bunch` return object will also have a ``frame`` member. .. versionadded:: 0.24 n_retries : int, default=3 Number of retries when HTTP errors are encountered. .. versionadded:: 1.5 delay : float, default=1.0 Number of seconds between retries. .. versionadded:: 1.5 Returns ------- data : :class:`~sklearn.utils.Bunch` Dictionary-like object, with the following attributes. data : {ndarray, dataframe} of shape (494021, 41) The data matrix to learn. If `as_frame=True`, `data` will be a pandas DataFrame. target : {ndarray, series} of shape (494021,) The regression target for each sample. If `as_frame=True`, `target` will be a pandas Series. frame : dataframe of shape (494021, 42) Only present when `as_frame=True`. Contains `data` and `target`. DESCR : str The full description of the dataset. feature_names : list The names of the dataset columns target_names: list The names of the target columns (data, target) : tuple if ``return_X_y`` is True A tuple of two ndarray. The first containing a 2D array of shape (n_samples, n_features) with each row representing one sample and each column representing the features. The second ndarray of shape (n_samples,) containing the target samples. .. versionadded:: 0.20 r&)r&r'r(r+r,rsnormal.Nri1 rrr r g?F)copyrshttpssmtp)r!z kddcup99.rstfetch_kddcup99)datatargetframe target_names feature_namesDESCR)r_fetch_brute_kddcup99r8r9r<r;np logical_notshaper randintr_c_logastypefloatshuffle_methodrrr )r%r&r r!r'r(r)r*r+r,kddcup99r8r9r<r;stnormal_samplesnormal_targetsabnormal_samplesabnormal_targetsn_samples_abnormalrfdescrr:s Z/var/www/html/test/jupyter/venv/lib/python3.11/site-packages/sklearn/datasets/_kddcup99.pyr7r76sut 222I$/ H =D _F*M(L ~~ j  N1  ad111:!!9-3A6),77  $6 = =+A.+A.u^%556~'778 ~~6))Vv-=-= BK1 uT!SbS&\4233</0%crc*]233-?? VT!!!Q$Z#-55e%5HHIIQQQT VT!!!Q$Z#-55e%5HHIIQQQT VT!!!Q$Z#-55e%5HHIIQQQT V  QQQT g%A7DAYF5aaadT!!!Q$Zaaad;>5aaadT!!!Q$ZaaadT!!!Q$ZGHDa a a a MO%dFNNN f  ' 'F E 5 dFM<  tVV|  !#    ct|}d}|rt|d|z}t}nt|d|z}t}t|d}t|d} t |} gdt fdd d d t fd t fd t fdt fdt fdt fdt fdt fdt fdt fdt fdt fdt fdt fdt fdt fdt fdt fdt fdt fdt fd t fd!t fd"t fd#t fd$t fd%t fd&t fd't fd(t fd)t fd*t fd+t fd,t fd-t fd.t fd/t fd0} d1| D} | d2} | d3d2}| r^ tj|}tj| }n*#t$r&}td4t|d5|d3}~wwxYw|rt|td6|jzt!||||7t#j| }td8t||j}t+|d9:}g}|D]R}|}||d;d<d=S|td>t9j|t#j|t>?}tAd@D].}|d3d3|f!|||d3d3|f</|d3d3d3d2f}|d3d3d2f}tj"||dABtj"|| dABntdCtG|||| gDS)Ea5Load the kddcup99 dataset, downloading it if necessary. Parameters ---------- data_home : str, default=None Specify another download and cache folder for the datasets. By default all scikit-learn data is stored in '~/scikit_learn_data' subfolders. download_if_missing : bool, default=True If False, raise an OSError if the data is not locally available instead of trying to download the data from the source site. percent10 : bool, default=True Whether to load only 10 percent of the data. n_retries : int, default=3 Number of retries when HTTP errors are encountered. delay : float, default=1.0 Number of seconds between retries. Returns ------- dataset : :class:`~sklearn.utils.Bunch` Dictionary-like object, with the following attributes. data : ndarray of shape (494021, 41) Each row corresponds to the 41 features in the dataset. target : ndarray of shape (494021,) Each value corresponds to one of the 21 attack types or to the label 'normal.'. feature_names : list The names of the dataset columns target_names: list The names of the target columns DESCR : str Description of the kddcup99 dataset. r1z-py3 kddcup99_10rIsamplestargetsduration) protocol_typeS4)serviceS11)flagS6 src_bytes dst_byteslandwrong_fragmenturgenthotnum_failed_logins logged_innum_compromised root_shell su_attemptednum_rootnum_file_creations num_shellsnum_access_filesnum_outbound_cmds is_host_loginis_guest_logincount srv_count serror_ratesrv_serror_rate rerror_ratesrv_rerror_rate same_srv_rate diff_srv_ratesrv_diff_host_ratedst_host_countdst_host_srv_countdst_host_same_srv_ratedst_host_diff_srv_ratedst_host_same_src_port_ratedst_host_srv_diff_host_ratedst_host_serror_ratedst_host_srv_serror_ratedst_host_rerror_ratedst_host_srv_rerror_rate)labelsS16cg|] }|d S)r).0cs rS z)_fetch_brute_kddcup99..ps%%%QAaD%%%rTNz7The cache for fetch_kddcup99 is invalid, please delete z! and run the fetch_kddcup99 againzDownloading %s)dirnamer+r,zextracting archiverQ)rmode ,zextraction done)dtype*r)compressz1Data not found and `download_if_missing` is False)r8r9r<r;)$rrARCHIVE_10_PERCENTARCHIVErintrGjoblibload ExceptionOSErrorstr_mkdirploggerinforrr?rdebugrr readlinesdecodeappendreplacesplitcloseosremoveasarrayobjectrangerFdumpr )r&r(r'r+r, dir_suffix kddcup_dirarchive samples_path targets_path availabledt column_namesr;r<XyeDT archive_pathfile_Xylinejs rSr>r> sV 222IJ)]Z%?@@ $)Z*%<==  I..L I..L|$$I+  S+ +  +   +  c +  c +   +  3+  3+   +  c"+  c+  C +  s+  +  S!+ " s##+ $ s%+ & S!'+ ( c")+ * #++ , 3-+ . #/+ 0 c1+ 2 3+ 4 E"5+ 6 7+ 8 E"9+ : % ;+ < % =+ > u%?+ @ 3A+ B s#C+ D "5)E+ F "5)G+ H '.I+ J '.K+ L 'M+ N $U+O+ P 'Q+ R $U+S+ T U+ BZ&%"%%%L#L "%M'K  L))A L))AA   Fz??FFF   K  $w{2333gzYeTTTT Xb\\ )***J(899 ,S999 OO%% 9 9D;;==D IIdll4,,22377 8 8 8 8  &''' , Z& ) ) )r . .A!!!Q$xr!u--Bqqq!tHH qqq#2#vJ qqq"uI  A|a0000 A|a00000IJJJ  #"^    s:(H$$ I.!IIc tj|dS#t$r!}|jtjkrYd}~dSd}~wwxYw)zgEnsure directory d exists (like mkdir -p on Unix) No guarantee that the directory is writable. N)rmakedirsrerrnoEEXIST)drs rSrrs] A  7el " "  # " " " " "s A>A)NTTr.r/))__doc__rloggingrgziprnumbersrros.pathrrrnumpyr?utilsr r r rHutils._param_validationr r rrr_baserrrrrr getLogger__name__rrPathLiker7r>rrrTrSrs  """""""" --------------KKKKKKKKKK   8 O   (' 8 O  8 $ $::::;;TB2;-;'([ ){ kKhxD@@@A(4d9===>  #'"    BBBBBLRUXXXXvrT