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)"

.94046230:5:0: .93927690:4:9: .94380660:4:8: .93910240:4:8: .94977130:8:3: .94563730:4:9: .94903650:4:3: .95492930:2:5: .95692350:4:9: .94804320:4:9:
.94021870:4:8: .93805740:5:9: .94136780:2:3: .93829440:2:8: .94832200:7:3: .94433860:5:9: .94694240:2:8: .95482370:4:5: .95304560:5:9: .94804320:5:9:
.94017460:2:0: .93676680:8:3: .94126470:5:8: .93564090:7:8: .94593440:2:5: .94316830:10:9: .94511800:5:3: .95364730:5:5: .95026730:2:9: .94692670:2:8:
.93680420:10:3: .93675250:7:9: .94111830:10:3: .93548410:8:8: .94590170:10:3: .94316830:7:9: .94163820:7:1: .95190170:8:5: .94815290:7:9: .94675360:7:9:
.93677370:7:3: .93521780:10:9: .93980250:8:3: .93546950:10:8: .94562870:4:3: .94316830:8:9: .94151830:8:1: .95072520:7:5: .94746310:10:9: .94516740:8:8:
.93677370:8:3: .93082290:2:3: .93978810:7:3: .93487510:1:8: .94447920:5:3: .94307010:2:9: .93883170:1:3: .95071120:10:5: .94708910:8:9: .94502080:10:8:
.93439650:100:8: .92309810:1:9: .93870110:1:3: .93417030:5:8: .94338150:1:5: .94165590:1:9: .93874410:10:1: .94892590:1:3: .94369970:1:2: .94473770:100:7:
.93023940:1:7: .91846370:100:3: .93124650:100:3: .92870910:100:6: .94283780:100:3: .94092880:100:9: .93182510:100:0: .94296720:100:5: .94369300:100:9: .93911700:1:1:
.89614590:0.1:7: .88932910:0.1:9: .91437930:0.1:8: .91388580:0.1:3: .90243210:0.1:7: .89679670:0.1:4: .88604940:0.1:3: .90620470:0.1:9: .90222720:0.1:2: .89623910:0.1:7:
.87530820:0.001:7: .86419240:0.001:9: .88590080:0.001:8: .88718260:0.001:3: .86611080:0.001:7: .87970970:0.001:4: .86190840:0.001:3: .87621860:0.001:9: .87014740:0.001:3: .85904360:0.001:7: