model6.mdl

文本分类算法

SVM-light Version V3.50
0 # kernel type
1 # kernel parameter -d 
1 # kernel parameter -g 
1 # kernel parameter -s 
0 # kernel parameter -r 
EmptyParam # kernel parameter -u 
1000 # highest feature index 
418 # number of training documents 
170 # number of support vectors plus 1 
1.0706893 # threshold b 
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0.99999993212504223 3:0.126415 5:0.098283 17:0.054373998 104:0.047265001 193:0.088867001 200:0.101299 231:0.088867001 240:0.126415 248:0.202599 253:0.079149999 294:0.126415 297:0.104719 334:0.088867001 361:0.119048 383:0.202599 396:0.104719 397:0.101299 443:0.126415 452:0.085202999 473:0.069220997 474:0.108666 509:0.126415 514:0.074258 540:0.136797 555:0.136797 579:0.108666 590:0.080534004 617:0.075396001 627:0.108666 637:0.126415 664:0.113334 681:0.075396001 686:0.35714501 709:0.108666 741:0.113334 748:0.108666 780:0.113334 790:0.104719 796:0.104719 797:0.379244 811:0.126415 817:0.074258 826:0.113334 827:0.119048 850:0.090916999 857:0.167101 870:0.108666 882:0.27359399 900:0.073168002 920:0.113334 927:0.055419002 931:0.113334 979:0.226669 
0.55087583455493305 54:0.063444003 89:0.117258 93:0.045582 104:0.065761998 121:0.055211999 134:0.052561998 155:0.040335 161:0.105125 165:0.058628999 170:0.033449002 172:0.088661999 179:0.018777 193:0.041214999 213:0.055211999 228:0.048567001 240:0.058628999 253:0.036708001 265:0.046980999 283:0.058628999 294:0.058628999 300:0.055211999 302:0.115174 316:0.048567001 323:0.041214999 328:0.091164 334:0.041214999 344:0.063444003 349:0.082429998 355:0.042165998 363:0.030152 364:0.048567001 369:0.050397001 370:0.038029 375:0.058628999 393:0.050397001 395:0.048567001 396:0.048567001 415:0.063444003 420:0.118547 424:0.076058 429:0.041214999 445:0.026208 446:0.19426601 447:0.12688801 457:0.058628999 461:0.055211999 466:0.044330999 468:0.036708001 474:0.100794 475:0.043198999 476:0.063444003 497:0.037349999 514:0.034439001 517:0.037349999 525:0.055211999 583:0.052561998 597:0.063444003 599:0.16051701 600:0.063444003 640:0.052561998 652:0.046980999 658:0.496912 666:0.046980999 673:0.065070003 679:0.076058 681:0.034967002 686:0.22085001 697:0.048567001 706:0.040335 713:0.114088 726:0.055211999 732:0.048567001 734:0.044330999 736:0.055211999 738:0.050397001 744:0.063444003 749:0.058628999 790:0.048567001 808:0.036708001 824:0.055211999 826:0.052561998 827:0.22085001 838:0.063444003 848:0.061788999 855:0.034967002 857:0.387492 859:0.19426601 866:0.105125 877:0.055211999 878:0.091164 880:0.052561998 882:0.12688801 900:0.033934001 910:0.058628999 915:0.068879001 927:0.025702 934:0.044330999 936:0.190332 937:0.042165998 973:0.091164 979:0.052561998 993:0.063444003 
0.99999993212504223 54:0.16375899 89:0.075664997 106:0.023536 164:0.16375899 195:0.065040998 223:0.15132999 230:0.065040998 233:0.075664997 254:0.075664997 276:0.041988999 282:0.16375899 300:0.14251199 302:0.037160002 309:0.041432001 330:0.023536 334:0.053190999 393:0.065040998 402:0.057211999 441:0.062679 446:0.062679 468:0.047375001 481:0.046588998 499:0.060632002 504:0.046588998 506:0.062679 509:0.075664997 526:0.15132999 557:0.065040998 583:0.067836002 595:0.081878997 599:0.041432001 616:0.067836002 617:0.090255998 637:0.075664997 673:0.37790301 686:0.427535 739:0.058827002 745:0.062679 754:0.15132999 772:0.050009001 796:0.25071499 826:0.067836002 827:0.21376701 839:0.075664997 853:0.065040998 857:0.50008798 868:0.044447001 905:0.067836002 915:0.044447001 927:0.066342004 949:0.058827002 
0.99999993212504223 8:0.055682998 104:0.046114001 106:0.15346301 107:0.110576 115:0.084853001 161:0.110576 165:0.123338 193:0.086704999 206:0.059907001 213:0.116151 233:0.123338 237:0.123338 253:0.077224001 287:0.123338 293:0.053555001 294:0.123338 299:0.095890999 301:0.133468 304:0.069388002 334:0.26011401 336:0.133468 343:0.106021 375:0.123338 412:0.110576 420:0.083129004 445:0.055133998 446:0.10217 447:0.133468 460:0.133468 475:0.090878002 481:0.075942002 517:0.078575 542:0.088703997 584:0.081517003 587:0.123338 604:0.133468 616:0.110576 639:0.116151 643:0.123338 664:0.110576 665:0.086704999 686:0.580755 688:0.061960999 717:0.081517003 732:0.10217 734:0.093258999 769:0.116151 797:0.123338 815:0.106021 827:0.116151 877:0.116151 887:0.069388002 924:0.077224001 927:0.05407 932:0.123338 937:0.088703997 948:0.086704999 964:0.077224001 999:0.074722998 
0.92327589209093797 8:0.069760002 14:0.14551599 60:0.138532 93:0.120135 106:0.048064999 124:0.167211 146:0.132825 293:0.067094997 323:0.108625 330:0.096130997 334:0.108625 361:0.14551599 376:0.14551599 396:0.128001 407:0.167211 429:0.108625 439:0.15452 445:0.069072999 446:0.128001 481:0.095141999 525:0.14551599 548:0.138532 549:0.106306 585:0.167211 596:0.138532 659:0.123821 665:0.108625 671:0.14551599 681:0.092159003 686:0.14551599 716:0.132825 734:0.35051101 738:0.132825 805:0.379435 853:0.132825 857:0.204252 859:0.128001 874:0.14551599 887:0.086929999 900:0.089435004 915:0.090768002 927:0.20322099 945:0.15452 975:0.132825 985:0.106306 999:0.093615003 
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-0.30465503706888486 45:0.18673199 249:0.373465 258:0.166903 276:0.115584 294:0.20828401 302:0.102291 304:0.117176 309:0.11405 369:0.17904 416:0.13766 475:0.153468 670:0.20828401 686:0.58844 739:0.161934 787:0.20828401 796:0.172537 827:0.19614699 841:0.22539 857:0.13766 975:0.17904 
-0.050196123973044585 45:0.164011 63:0.107462 222:0.18294001 230:0.15725499 249:0.328022 255:0.125857 359:0.125857 369:0.15725499 436:0.18294001 444:0.077233002 477:0.13157 516:0.164011 553:0.17228 596:0.164011 610:0.14223 664:0.164011 665:0.12860399 686:0.34455901 716:0.15725499 719:0.164011 805:0.17968901 806:0.31450999 857:0.48363701 
-0.88165294090986968 8:0.106601 106:0.073449001 109:0.25551701 184:0.20297199 237:0.23612399 357:0.22236399 398:0.195599 446:0.195599 599:0.12929399 686:0.444729 688:0.118621 736:0.22236399 769:0.22236399 797:0.23612399 804:0.30632001 808:0.14783999 812:0.25551701 853:0.20297199 857:0.15606 882:0.25551701 
-0.3358850107538085 5:0.200716 104:0.19305 106:0.080306001 107:0.231454 209:0.206875 294:0.258167 380:0.161642 397:0.206875 475:0.190222 501:0.14729001 506:0.21385799 552:0.24312299 574:0.137756 677:0.221919 686:0.48624501 739:0.200716 805:0.126789 829:0.258167 848:0.136041 855:0.153975 857:0.170628 900:0.149425 
0.99999993212504223 104:0.107838 121:0.271617 179:0.092373997 224:0.28842399 265:0.231121 344:0.312112 364:0.238923 435:0.271617 473:0.157932 574:0.153901 595:0.312112 665:0.202757 673:0.16005699 695:0.22424001 884:0.24792901 950:0.28842399 954:0.22424001 956:0.28842399