Comments (2)
From libsvm/matlab/README
Note that the order of classes here is the same as 'Label' field
in the model structure.
tjusxh writes:
In pred_estimates, the position of the maximum value in one row
is not the pred_label.prob_estimates=0.0877046072932294 0.00689885694870784
0.0510358500866629 0.0349193526856883 0.0201649925974930
0.0572772003038145 0.00354058458641571 0.434801642194089
0.299917382939861 0.00373953036403846
0.0569029578292815 0.0128889675010719 0.0226503273265042
0.235434067349005 0.0274432928060539 0.0223993134855364
0.00449010998588290 0.372552666098744 0.240135267815857
0.00510302980206350
0.0202618302729419 0.00609933422466536 0.00513096031248623
0.556599397170814 0.00770208398129837 0.0147579801297493
0.00117991662750405 0.123657362841668 0.263114176688193
0.00149695775068038
0.0138081408458132 0.0134109236889526 0.0261085782234978
0.379193740840643 0.0136879003688169 0.0278073190536115
0.00393368980397517 0.0770472704849993 0.441814426316247
0.00318801037344396
0.00737713942130312 0.00719604777712997 0.0190913916210304
0.766244252381808 0.00452925052833849 0.00832667922291313
0.000954117402067928 0.0242901169949015 0.160638180981833
0.00135282366867416
0.0404892166770354 0.0131597503809068 0.00812199404116744
0.0709609923235642 0.0256930503037581 0.0235279018153220
0.00310139828330843 0.190031347957460 0.620513527363689
0.00440082085378811
0.0233835236239888 0.00845191161599723 0.0204935753653564
0.0455692904676819 0.0733235759739852 0.0506628894366520
0.00506885299370543 0.0616635058140948 0.707636494571399
0.00374638013713891
0.0170375648555056 0.0117320006702165 0.0351611195497132
0.0329173319877270 0.0199963414010635 0.0233994742806957
0.00202927477235737 0.0367208285826699 0.809862937232914
0.0111431266671378
0.00249398437648049 0.00118775906267820 0.00420318445065694
0.00150617919781232 0.00851998127528923 0.0170565271724271
0.000216428383816490 0.00376026537283618 0.959633934361137
0.00142175634686587
0.0172952090357666 0.00203085205048888 0.0663402503175806
0.00337260286616463 0.0192039462603744 0.0368582111255392
0.00135917901052383 0.0574097352946263 0.753632624031509
0.0424973900074269
0.000537446336879699 2.15124069324038e-05 0.00561621351527447
0.00185702285684450 8.83922926914827e-05 0.000224499754837717
3.52901270154285e-05 7.98180192575826e-06 0.00140238264873741
0.990209258258861
0.00800564331385912 0.000723560253424673 0.00910529583487216
0.0517704592247967 0.00127130082212482 0.000836563684457387
0.0318391492343732 0.00144605301838154 0.00150543142470253
0.893496543189008
0.00597297494217007 0.00213978859351707 0.0254911330116816
0.0667699924629301 0.00264826602958697 0.00124512773832485
0.0281686476611874 0.00111821134747100 0.00185613966496867
0.864589718548163
0.737566350619235 0.00377211871885958 4.93077713563539e-05
0.00382722305898168 0.000840960416034537 7.15881072403622e-05
0.000763927380789079 0.000475734513815691 0.000236976483126986
0.252395812930561
0.485882559427058 0.179818235887341 0.00491168109845924
0.0735388345615359 0.0108076830998238 0.00347030734890046
0.00671528385336261 0.0153990089988476 0.00948964326287568
0.209966762461795pred_label=6
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7—
Reply to this email directly or view it on GitHub.*
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@cjlin1 Thank you very much. I am not careful.
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