temp.train.txt.model

Multiple INstance Learning Library

1.152771474562962 25:0.055963 394:0.055963 423:0.055963 853:0.055963 963:0.218 1730:0.055963 1740:0.11045 2294:0.055963 2658:0.055963 3990:0.055963 4766:0.055963 6063:0.055963 7318:0.055963 44976:0.055963 
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0.8266808901467596 3593:0.25 7003:0.25 12168:0.25 23875:0.25 
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1.420588440785656 19:0.055637 62:0.055637 78:0.055637 198:0.055637 441:0.055637 770:0.055637 910:0.055637 1041:0.055637 1209:0.10981 1511:0.055637 1640:0.055637 3617:0.055637 3780:0.055637 5481:0.055637 10284:0.055637 10835:0.055637 15571:0.055637 
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1.186080205930183 268:0.12855 309:0.062246 608:0.062246 718:0.062246 722:0.062246 748:0.062246 979:0.062246 1209:0.062246 1282:0.062246 1384:0.062246 1562:0.062246 1750:0.062246 4380:0.062246 5560:0.062246 14608:0.062246 
0.8795778766465239 244:0.055719 268:0.10997 979:0.055719 1209:0.055719 1282:0.055719 1384:0.055719 1550:0.055719 1562:0.055719 1706:0.055719 3171:0.055719 4380:0.055719 4995:0.055719 5560:0.055719 11830:0.055719 14608:0.10997 42487:0.055719 
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0.7514690802645615 53:0.047619 62:0.047619 67:0.047619 260:0.047619 302:0.047619 335:0.047619 544:0.047619 608:0.047619 790:0.047619 791:0.047619 1069:0.047619 1320:0.047619 1743:0.047619 1976:0.047619 3421:0.047619 4884:0.047619 5712:0.047619 6458:0.047619 6950:0.047619 9382:0.047619 20591:0.047619 
2.015716373176253 188:0.089285 218:0.043233 286:0.043233 302:0.043233 309:0.043233 346:0.043233 418:0.043233 427:0.043233 435:0.043233 627:0.043233 705:0.043233 1418:0.043233 2868:0.043233 3974:0.043233 7451:0.043233 7957:0.089285 8837:0.043233 10578:0.043233 13106:0.043233 18983:0.043233 26753:0.043233 
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1.621582714674768 10:0.071429 14:0.071429 40:0.071429 102:0.071429 126:0.071429 267:0.071429 766:0.071429 783:0.071429 916:0.071429 1239:0.071429 2726:0.071429 3657:0.071429 5136:0.071429 7073:0.071429 
2.876334639832718 102:0.059006 126:0.059006 267:0.059006 283:0.059006 420:0.059006 423:0.059006 449:0.059006 465:0.059006 478:0.11646 666:0.059006 766:0.059006 1582:0.059006 1950:0.059006 3992:0.11646 13626:0.059006 
0.2153526427246114 31:0.2 805:0.2 1694:0.2 3988:0.2 6528:0.2 
0.2248515297553171 40:0.049676 48:0.049676 224:0.049676 436:0.049676 441:0.049676 645:0.049676 750:0.049676 852:0.10259 862:0.049676 1021:0.049676 1138:0.049676 1471:0.049676 2468:0.049676 3657:0.10259 3990:0.049676 6310:0.049676 7065:0.049676 9394:0.049676 
1.215958399415959 9:0.043355 33:0.043355 65:0.043355 78:0.043355 268:0.043355 300:0.043355 341:0.043355 545:0.043355 572:0.043355 663:0.043355 768:0.043355 841:0.043355 1267:0.043355 1345:0.043355 1346:0.043355 1592:0.043355 2479:0.043355 3320:0.089537 3480:0.043355 4425:0.043355 5146:0.043355 35119:0.043355 
0.7676578052803812 65:0.045238 198:0.045238 304:0.045238 341:0.14048 439:0.045238 663:0.045238 841:0.045238 1346:0.045238 1862:0.045238 2479:0.045238 3320:0.045238 3704:0.045238 5146:0.045238 5560:0.045238 7185:0.045238 7957:0.045238 12516:0.045238 13649:0.045238 24231:0.045238 35119:0.045238 
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0.1170678339568132 40:0.04 82:0.04 116:0.04 198:0.04 309:0.04 405:0.04 531:0.04 744:0.04 746:0.04 1386:0.04 1489:0.04 1706:0.04 1881:0.04 2437:0.04 2748:0.04 3070:0.04 3704:0.04 3737:0.04 4415:0.04 4790:0.04 4799:0.04 4987:0.04 5047:0.04 15669:0.04 35120:0.04 
2.551083818524243 40:0.047619 82:0.047619 116:0.047619 332:0.047619 744:0.047619 1328:0.047619 1386:0.047619 1706:0.047619 2151:0.047619 2437:0.047619 2500:0.047619 3674:0.047619 3737:0.047619 3869:0.047619 4255:0.047619 4987:0.047619 5047:0.047619 6865:0.047619 15669:0.047619 26536:0.047619 35120:0.047619 
0.7751994044534207 62:0.125 711:0.125 791:0.125 1217:0.125 2243:0.125 2334:0.125 5813:0.125 38866:0.125 
1.521243061920699 13:0.05 103:0.05 110:0.05 188:0.05 439:0.05 491:0.05 916:0.05 1039:0.05 1078:0.05 1243:0.05 2278:0.05 3566:0.05 3743:0.05 5018:0.05 5491:0.05 11047:0.05 11048:0.05 27719:0.05 27720:0.05 29197:0.05 
3.411071471022859 289:0.043478 295:0.043478 372:0.043478 373:0.043478 486:0.043478 646:0.043478 711:0.043478 771:0.043478 852:0.043478 978:0.043478 1640:0.043478 1701:0.043478 2840:0.043478 2849:0.043478 3873:0.043478 5061:0.043478 5424:0.043478 7286:0.043478 7428:0.043478 13114:0.043478 14577:0.043478 22281:0.043478 30242:0.043478 
9.65494517473034 62:1 
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0.09055414848562586 103:0.043355 126:0.043355 260:0.043355 489:0.043355 523:0.043355 587:0.043355 629:0.043355 656:0.043355 705:0.043355 732:0.043355 790:0.043355 861:0.043355 1267:0.043355 2511:0.043355 3320:0.043355 7242:0.043355 7283:0.043355 8189:0.043355 11012:0.043355 38853:0.089537 52586:0.043355 52587:0.043355 
0.06583304928878872 56:0.045054 78:0.045054 317:0.045054 735:0.093045 805:0.045054 1120:0.093045 2357:0.093045 2639:0.045054 3008:0.045054 3913:0.045054 3987:0.045054 3988:0.045054 3992:0.045054 5982:0.045054 7072:0.045054 7715:0.045054 8778:0.045054 10214:0.045054 17239:0.045054 
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