我正在使用的是此页面：http://svmlight.joachims.org/
Mac OS X（新）：http://download.joachims.org/svm_light/current/svm_light_osx.8.4_i7.tar.gz
按照说明安装后，我跳进了他的例子：Inductive SVM（文档在同一页面上）
$ ./svm_learn example1/train.dat example1/model
Scanning examples...done
Reading examples into memory...100..200..300..400..500..600..700..800..900..1000..1100..1200..1300..1400..1500..1600..1700..1800..1900..2000..OK. (2000 examples read)
Setting default regularization parameter C=1.0000
Optimizing........................................................................................................................................................................................................................................................................................................................................................................................................................................done. (425 iterations)
Optimization finished (5 misclassified, maxdiff=0.00085).
Runtime in cpu-seconds: 0.07
Number of SV: 878 (including 117 at upper bound)
L1 loss: loss=35.67674
Norm of weight vector: |w|=19.55576
Norm of longest example vector: |x|=1.00000
Estimated VCdim of classifier: VCdim<=383.42791
Computing XiAlpha-estimates...done
Runtime for XiAlpha-estimates in cpu-seconds: 0.00
XiAlpha-estimate of the error: error<=5.85% (rho=1.00,depth=0)
XiAlpha-estimate of the recall: recall=>95.40% (rho=1.00,depth=0)
XiAlpha-estimate of the precision: precision=>93.07% (rho=1.00,depth=0)
Number of kernel evaluations: 45954
Writing model file...done
$ ./svm_classify example1/test.dat example1/model example1/predictions
Reading model...OK. (878 support vectors read)
Classifying test examples..100..200..300..400..500..600..done
Runtime (without IO) in cpu-seconds: 0.00
Accuracy on test set: 97.67% (586 correct, 14 incorrect, 600 total)
Precision/recall on test set: 96.43%/99.00%
有谁知道这是不是应该是什么？ 如果没有，我该如何解决这个问题才能让它运作良好？
仅供参考，我使用OSX 10.9和python 2.7.5。