1. Each columns corresponds to a single run.
2. Each row of a column corresponds to a cross-validation split.
3. Each entry is of the form "validation set accuracy:svm C:ignore this (testing was done with the model which was trained on that split)"

.90996400:1:6: .92745650:1:9: .92869110:4:6: .91857670:2:5: .89972460:2:2: .92133000:1:1: .92337050:7:9: .90310630:4:8: .90654520:4:9: .92587050:5:5:
.90815670:2:6: .91996400:2:5: .92868100:7:6: .91847590:1:5: .89671700:1:8: .91643070:2:9: .92000690:8:9: .90228770:10:1: .90359420:8:7: .92477090:8:5:
.90538220:4:8: .91770740:10:5: .92713130:10:6: .91192560:4:5: .88892320:4:2: .91308130:8:9: .91833280:10:2: .90228770:8:1: .90318710:5:9: .92383480:10:1:
.89872530:5:8: .91577550:0.001:2: .92689530:8:6: .91192560:5:5: .88796820:0.001:8: .91307180:4:9: .91814710:4:2: .90138210:2:8: .90292530:1:9: .92307590:7:5:
.89847210:7:8: .91577550:0.1:2: .92680430:5:6: .91018850:7:5: .88796820:0.1:8: .91292490:7:9: .91814710:5:2: .90074930:5:1: .90192750:10:7: .92252230:4:5:
.89832980:8:8: .91452950:7:5: .92598560:2:6: .90962350:8:5: .88569410:5:2: .91103280:10:9: .91813850:2:9: .90055330:7:6: .90183980:7:9: .91927150:2:6:
.89683430:0.001:3: .91452950:8:5: .92190600:1:6: .90778850:0.001:3: .88320540:100:9: .90931610:5:9: .91407220:1:9: .90009910:1:8: .90095560:2:9: .91627690:100:3:
.89683430:0.1:3: .91336660:4:9: .91746100:0.001:6: .90778850:0.1:3: .88093370:10:9: .89877800:100:9: .90509180:100:9: .89544900:0.001:8: .90082580:100:7: .91319600:1:6:
.89177730:10:0: .91206800:5:0: .91746100:0.1:6: .90499660:10:0: .88074570:7:2: .89752010:0.001:9: .90116520:0.001:9: .89544900:0.1:8: .89312180:0.001:9: .89016300:0.001:3:
.87742350:100:2: .91094640:100:0: .91034060:100:6: .90151630:100:0: .87958590:8:2: .89752010:0.1:9: .90116520:0.1:9: .89454170:100:2: .89312180:0.1:9: .89016300:0.1:3: