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HtJ LHH2H0H HCHN$ N,(IEI$IUI$H]LeLmÐUHAWAVAUATSH8HuUHUHHM芎9EH]AHcEHELuMcHC@HUUF<(HCH¨tHCHMHHDH}H{DuEEDA*YffZCAD9eHEH8[A\A]A^A_ÐUHAWAVAUATSH(IuAHUH@DA9~LMLmID$H¨tID$IHDLI|$ڋuHcffZADA9HEH([A\A]A^A_UHAWAVAUATSH(HAHcHuHGXEO@HUHH"S@9}T~PIALmHCH¨t HCIHDLH{DuIcffZADAD9c@S`HcHDh)щK`HSPHu 2E~E*HcH H{P47*YHsXHc<HuYA9H([A\A]A^A_ÐUHHG0 }fWEHO HcHHcHXEHOH4H<vYXEYEaÐUHATSHHGA H@HH@HtdLcHMtLqLaH{PHtcIHoLdH_Ha[A\ÐUHATSHH@ H@HH@HtcLcHMtLLyaH{PHt[cIHL#dHߥ[A\ÐUHH]LeHHH? H@HLg@MtLvL`H{HHtbIHwLcHgH`H$Ld$ÐUHH]LeHHHV? H@HLg@MtLL~`H{HHt`bIHL+cHH$Ld$UHATSHH/? H@HLgHMtL菊L`H{PHtaH{XHtaH{hHtaH{pHtaH{xHtaIHXLbHHH_[A\ÐUHATSHH> H@HLgHMtL߉Lg_H{PHtIaH{XHt;aH{hHt-aH{pHtaH{xHtaIH訣LaH蘣[A\ÐUHSHHG0EHGHcHHcHuHEHHHEHcHcslIc?VHUHHUIHEH8WIHUH:BTIE{lAAA{t%McN HSpJ LDMu?HcHI<IcH4LCpM0M@L8It5HItLLcIHcKHSpJ HT:JLcLHHSpJ :uOD ODAD9Sl>HUHHEHMHuLXUHuuHEHUHH 4 UIŻL%4 LuI<UIHLTHHPuHEL(H}qUHH[A\A]A^A_ÐUHSHH@, HtH3, HHHuH[ÐHVHUsage: model = svmtrain(training_label_vector, training_instance_matrix, 'libsvm_options'); libsvm_options: -s svm_type : set type of SVM (default 0) 0 -- C-SVC 1 -- nu-SVC 2 -- one-class SVM 3 -- epsilon-SVR 4 -- nu-SVR -t kernel_type : set type of kernel function (default 2) 0 -- linear: u'*v 1 -- polynomial: (gamma*u'*v + coef0)^degree 2 -- radial basis function: exp(-gamma*|u-v|^2) 3 -- sigmoid: tanh(gamma*u'*v + coef0) 4 -- precomputed kernel (kernel values in training_instance_matrix) -d degree : set degree in kernel function (default 3) -g gamma : set gamma in kernel function (default 1/num_features) -r coef0 : set coef0 in kernel function (default 0) -c cost : set the parameter C of C-SVC, epsilon-SVR, and nu-SVR (default 1) -n nu : set the parameter nu of nu-SVC, one-class SVM, and nu-SVR (default 0.5) -p epsilon : set the epsilon in loss function of epsilon-SVR (default 0.1) -m cachesize : set cache memory size in MB (default 100) -e epsilon : set tolerance of termination criterion (default 0.001) -h shrinking : whether to use the shrinking heuristics, 0 or 1 (default 1) -b probability_estimates : whether to train a SVC or SVR model for probability estimates, 0 or 1 (default 0) -wi weight : set the parameter C of class i to weight*C, for C-SVC (default 1) -v n : n-fold cross validation mode -q : quiet mode (no outputs) Error: cannot transpose training instance matrix Length of label vector does not match # of instances. Wrong input format: sample_serial_number out of range n-fold cross validation: n must >= 2 Cross Validation Mean squared error = %g Cross Validation Squared correlation coefficient = %g Cross Validation Accuracy = %g%% Error: label vector and instance matrix must be double Error: cannot generate a full training instance matrix Error: can't convert libsvm model to matrix structure: %s transposeUnknown option -%c fullError: %s XW)WXYRW\XYYYYWWY6XYxWVWYXY?Y@unknown svm typeunknown kernel typegamma < 0cache_size <= 0eps <= 0C <= 0p < 0specified nu is infeasiblenu <= 0 or nu > 1wCsvm_type %s kernel_type %s degree %d gamma %g coef0 %g nr_class %d total_sv %d rho %glabel %dprobAprobBnr_svSV %.16g 0:%d %d:%.8g rbc_svclinear%80ssvm_typeunknown svm type. kernel_typeunknown kernel function. degreegamma%lfcoef0nr_classtotal_sv: *.nu = %f C = %f epsilon = %f obj = %f, rho = %f nSV = %d, nBSV = %d Total nSV = %d nu_svcone_classepsilon_svrnu_svrpolynomialrbfsigmoidprecomputeddegree of polynomial kernel < 0shrinking != 0 and shrinking != 1probability != 0 and probability != 1one-class SVM probability output not supported yetModel doesn't contain information for SVR probability inference unknown text in model file: [%s] WARNING: using -h 0 may be faster WARNING: reaching max number of iterations optimization finished, #iter = %d Exceeds max_iter in multiclass_prob Prob. model for test data: target value = predicted value + z, z: Laplace distribution e^(-|z|/sigma)/(2sigma),sigma= %g WARNING: training data in only one class. See README for details. WARNING: class label %d specified in weight is not found Line search fails in two-class probability estimates Reaching maximal iterations in two-class probability estimates h}ŗ̣9Solver_NU6Solver6Kernel7QMatrix5SVC_Q11ONE_CLASS_Q5SVR_Q-q?$@-q=Hz>P?{Gzt?0A@@h㈵>-C6?|=number of return field is not correctcannot transpose SV matrixParameterstotalSVLabelProbAProbBnSVsv_coefSVs;VpGvGGG8GXcJGMiR UW@W`XjX`LYd\\]ab0"d*d3d0jdPdpddh8AhX;ixoikm( m ,n on s0 $tP tx ́ l l@ ` X D W ͙H Ph H @h f @@TP^ph* fP 0x @ @ 8 0` z nzRx DAC <vDAC \mDAC |]D*AC H$gDAC P$FAC P$I"AC ȃ$NAC R$< QAC WzPRx  $SAC DS AC dAC vGAC *AC 4SMAC AC J AC $AC DSAC L$dSAC PVAC &WAC $XAC Pl[AC [ AC 4 AC T AC tUAC  AC AC *]AC ] AC \7AC 4]AAC T3]AC tDAC >AC 8AC \'AC L$\/AC [_%AC H<_AC F\`4AC H$|`UAC r$bVAC P:AC LAC S$ cAC P$4AC P$\AC P$AC PdCAC Ldd` tJ`p @ P~`p ޼޹Pp *0 !1  o  H   X 8 oooPooo[! !!! ! ! ` @$ $   . > N ^ n ~ !!.!>!N!^!n!~!!!!!!!!!"".">"N"^"n"~"""""""""##.#>#N#^#n#~####!8AX GCC: (Ubuntu 4.4.3-4ubuntu5.1) 4.4.3.symtab.strtab.shstrtab.note.gnu.build-id.gnu.hash.dynsym.dynstr.gnu.version.gnu.version_d.gnu.version_r.rela.dyn.rela.plt.init.text.fini.rodata.eh_frame_hdr.eh_frame.gcc_except_table.ctors.dtors.jcr.data.rel.ro.dynamic.got.got.plt.data.bss.comment$20.o  (8 HH@ HoUo8doPPs  8 }XX ##P $ a        !p `!P 0P%u  p"] H P  X   #        !`! # * 8 E #[`!jh!x `$    $* A'! 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