lib64bnr2-2.0.3-4pclos2019T>D ,0@91499b51e533e89b4289af6faa0963356b4d22ea%wgL}_dq2[>2c?Sd   > #)0@ H P `   T x ^ (x89:FGHI X$Y0\T]d^bde$f'l)zCClib64bnr22.0.34pclos2019Bayesian Noise Reduction Librarylibbnr is an implementation of the Bayesian Noise Reduction (BNR) algorithm. All samples of text contain some degree of noise (data which is either intentionally or unintentionally irrelevant to accurate statistical analysis of the sample where removal of the data would result in a cleaner analysis). The Bayesian noise reduction algorithm provides a means of cleaner machine learning by providing more useful data, which ultimately leads to better sample analysis. With the noisy data removed from the sample, what is left is only data relevant to the classification. libbnr can be linked in with your classifier and called using the standard C interface.]localhostYPCLinuxOSGPLSystem/Librarieshttp://bnr.nuclearelephant.com/linuxx86_64H A큤]]]A=841d688494f2f2e66252137592cea9c8ccb3c0431c984c0094f8ea07e139c37clibbnr.so.2.0.0rootrootrootrootrootrootrootrootlibbnr-2.0.3-4pclos2019.src.rpmlibbnr.so.2()(64bit)lib64bnr2lib64bnr2(x86-64)  @@@@@@ rpmlib(PayloadFilesHavePrefix)rpmlib(CompressedFileNames)libc.so.6()(64bit)libc.so.6(GLIBC_2.14)(64bit)libc.so.6(GLIBC_2.2.5)(64bit)libc.so.6(GLIBC_2.3.4)(64bit)libc.so.6(GLIBC_2.4)(64bit)rtld(GNU_HASH)rpmlib(PayloadIsXz)4.0-13.0.4-15.2-14.8.1]YFtex - 2.0.3-4pclos2019bb2 - 2.0.3-3pclos2017- rebuild against updates- rebuild for 2017localhost 15711338682.0.3-4pclos20192.0.3-4pclos2019libbnr.so.2libbnr.so.2.0.0lib64bnr2README/usr/lib64//usr/share/doc//usr/share/doc/lib64bnr2/-O2 -pipe -Wformat -Wp,-D_FORTIFY_SOURCE=2 -fstack-protector --param=ssp-buffer-size=4cpioxz5x86_64-mandriva-linux-gnumqwC]ӁB?7zXZi"6!t/[] cL A Ra .K}üzv1HqV͚5E=UՆ"E5Isp h_"C o x'$\I̤fk$_FSK|Oў' scQƌssbq>@N478b@L0SAK;ީm50iyS2̲5/q 0añE{al_:3^6&zB<,>2#Q,]u>Γd\{$ޕؼs/ɉ {ޏX/@乃3`K*%c5gVyZDO&{LV+er7qy'܄_u t[<f|Ԃ4*u4NbU&A^OH5X[mAe=5_ w48MzWZ{_{ۤ} ¨a͈gP]ſꐨW/QlggK |RM]=t1f,(ggWeQ H|[r0^SC)ͬuW\ QeCa5)7h O][8銺H6pdD؍d8;K<]e݇kJSj"Viz?R%??_ruS54E$h;d$8dkp )WՁ iHz$ 4L- xtۭٔxU-CMZD.317 KI|aߘ!I"$>F‹o Ԙ rv I9az}e~0wdUhD%SPc_#C:[T6EYC|8Q\R`[\*@eƙ5-2{)uq~#+XfuZ=`9TOr2Xڟ t&^)_ng.PX7g#Nӽ ^95_P8rXMgV>*/|+ eDsS0Ew+,qKs47ɑͱAcǹ\K ֘-: }eQ7)X>H~PzH',lV Ş_oӑ/ "HKżx;\d>8MQD%A֕OH#<Ȕ<1{aˣpmErzWQ>qd|L;SfQ BW]fE .yX'˳ݗӃ P<52C7{ɐ/ Xw-5CI{n @ ?S-nhNd+T,HG$G% cid#3CszWt7[!JlNI/ ^4ۅTlsN~{,x9Sfs >.q^ⰓE>B8"4[7SgNu:.Qc,R,Dw|(fA&,ő0@#0'\99?KfTάt%҃- ʠ3٦SɃˡBo(-U -w8_"gAuc[7Ok霗&qg1Þzj#V9Tĺ`@ 9C,J78Ĺ&DT͈78"+9Nn鎔C*2V4tK B, 7$N%̏{džӜ$ }gZ׼@cEѶ ":S>?BMؼiTz?}LۡI*7WӑIpzJ?ԽrqĸTb?>gU],?+Hy5[+Fm&%ά9"f>%&o/5Bc8.v~s2kIyE ÿؙ́`|T|1D|ޥRT _o_cP~䰖z ̩ v Bμg;h%Ik;a1ZlЁi9Z0" MLTEVQONMUx=="b4ϥ=Uߣa; "V$J4W6>{>PM |0?k( mSl`_Mep]ыn{x6sXkDE{؇`q9PKvuYB|]fɩ\'nOsE[bQhETCj]`BAe3nc"fXǍ' LO?mlyDSh*@*I^c0hxeeNEjD{tlh{i%}8#b{,>d%4ȭxb z1<$MgkCs&7*<ȭi{{zүtsɽ$)~ʯdOi~\l0M:l0@t'-JPwgF 8FP5Ja,fᬪ }j;;&3tɊ= K`5N;DږOxg:boL杘~t EfW+,}Oh! T)!-b̤X__e'(Kpp$g`^>J1X'k{{IX,Z 3 EK֔LpF!i%beZStc!y)AC"yL?Bd~394A@ƽ,)֒ۑSDʣb_^H4PZD|:Zفnac>w:LQaXC80cWfjAYc|qpgoe%Hmaa |%~ 43**X *8wg]#峻HɑL-24D,JTDxOWW)ZH۪Yڻ*.r=UCnҐHDzuRYj6 WYoeJG Bӈd˱ɕ6kL16bg(knNiDI%% =X*% :0qxKÑ0W87>.O-nCdyiL2|>0y8 &\ZĮf T O5?@%M`y"T )-fq^FIuK/7. r**x7:,5QBmpߜc|+7mkvEb 4~~u`#p},A)]ڀȘG/{RI&,1Wch\Wޥ2`o~cP}R ` J$Y*ۢ:Lg9Fȧ> o,}7koGה?٦t)r "ʳWO@TGQ ?-רlMy+TSTч5$\[i޿^+ف( {VLooc$ h[g#7ro>tR$}$wZ+j,0 ^l_nr &+Ȓ0BseQ7Ĺ^B}Kvh\T,HG+ػ XU s:$:>>=ޮ2t*s\8~ +7ی`*BM߀ ZQc-մ#r\9-h0 ;1;EJ׬sPN /#p9肑j~;^7>E|k;F֊;%5)_5 376LfM)'uqgT7~RݮC1Q8}c^K]kGy{q᧯ nH!{tDv2[qN3Lb;mziF腿"{ jd |{nz1NFkBAF7aH!Ӝaʄ*xL[BONCO>4l깾F:e .|@-߽ +}׷oxHrbd0v3?Ώ#D"= oͳT9uL0znw[bVn%6B!sQ!Q8 -&\<."߶> >=[2>j1`FG؁yaLFGoj"2LpX<εbTDZǏ# p5{zxa i]*mGIOdYo#I[! sXΟVϷ!6eFT JoY~G~ +7K\E8(H!JwiY0jќe;v j y]u7rn+/O[ !>nciQd֋%Z0m s%IR"B؃FHr^,(V։O uuz.FY>-qBugH4+;wj'%ي;^OG9c]PIU޸T*36„QLˁcZzM>wF۠ Q|, E9h@J0 gr?DQ)醞},!ER7MB\x1oƢd})Z6`/W1=qV A)QcgkbtWjw˜MCme+L_oGX; FW({cцGD q w0li$8t<9̈^AF̭U0R\jy8%]vxz!s->{r3/x<'?uXAN2U?yn盩nBS5̷XrZ>0 YZ