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Number of inactive variables = %ld Error: Kernel cache full! => increase cache sizeObjective function (over active variables): %.16f WARNING: Relaxing KT-Conditions due to slow progress! Terminating! Checking optimality of inactive variables... => (%ld SV (incl. %ld SV at u-bound), max violation=%.5f) POS=%ld, ORGPOS=%ld, ORGNEG=%ld POS=%ld, NEWPOS=%ld, NEWNEG=%ld Classifying unlabeled data as %ld POS / %ld NEG. %ld positive -> Added %ld POS / %ld NEG unlabeled examples. Model-length = %f (%f), loss = %f, objective = %f Increasing influence of unlabeled examples to %f%% .%ld positive -> Switching labels of %ld POS / %ld NEG unlabeled examples. Moving training errors to inconsistent examples... Now %ld inconsistent examples. Setting default regularization parameter C=%.4f WARNING: Using a kernel cache for linear case will slow optimization down!Optimization finished (maxdiff=%.5f). Runtime in cpu-seconds: %.2f (%.2f%% for kernel/%.2f%% for optimizer/%.2f%% for final/%.2f%% for update/%.2f%% for model/%.2f%% for check/%.2f%% for select) Number of SV: %ld (plus %ld inconsistent examples) Number of SV: %ld (including %ld at upper bound) Norm of weight vector: |w|=%.5f Norm of longest example vector: |x|=%.5f Number of kernel evaluations: %ld Error: Missing shared slacks definitions in some of the examples.'remove inconsistent' not available in this mode. Switching option off!Number of non-zero slack variables: %ld (out of %ld) %ld positive, %ld negative, and %ld unlabeled examples. Deactivating Shrinking due to an incompatibility with the transductive learner in the current version. Cannot compute leave-one-out estimates for transductive learner. Cannot compute leave-one-out estimates when removing inconsistent examples. Cannot compute leave-one-out with only one example in one class. Optimization finished (%ld misclassified, maxdiff=%.5f). Estimated VCdim of classifier: VCdim<=%.5f Computing XiAlpha-estimates...Runtime for XiAlpha-estimates in cpu-seconds: %.2f XiAlpha-estimate of the error: error<=%.2f%% (rho=%.2f,depth=%ld) XiAlpha-estimate of the recall: recall=>%.2f%% (rho=%.2f,depth=%ld) XiAlpha-estimate of the precision: precision=>%.2f%% (rho=%.2f,depth=%ld) Leave-One-Out test on example %ld Leave-one-out estimate of the error: error=%.2f%% Leave-one-out estimate of the recall: recall=%.2f%% Leave-one-out estimate of the precision: precision=%.2f%% Actual leave-one-outs computed: %ld (rho=%.2f) Runtime for leave-one-out in cpu-seconds: %.2f Constructing %ld rank constraints... (single %f) (joint %f) inconsistent(%ld)..Writing alpha file...w%.18g doneWriting prediction file...%.8g:+1 %.8g:-1 %.8g:-1 %.8g:+1 Calculating model... Cache-size in rows = %ld Kernel evals so far: %ld Reorganizing cache...done.%ld..done Running optimizer... Shrinking...Iteration %ld: Selecting working set... (i-step)(j-step on %ld) %ld vectors chosen pos ratio = %f (%f). Retraining.Number of switches: %ld Optimizingdone. 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