Skip to main content

Table 27 Combining and filtering features for training RBF-epsilon regression SVM model on dataset2431 and on dataset579

From: Improving model predictions for RNA interference activities that use support vector machine regression by combining and filtering features

   train2431 train579
    test579 test2431 10 × cross val   test2431 test579 10 × cross val
Method(s) t- test FN2431 R MSE R MSE FN579 R MSE R MSE
1 0 84(84) 0.509 0.095 0.711 0.026 84(84) 0.484 0.054 0.562 0.079
1 2 45(43.9) 0.494 0.100 0.687 0.027 22(21) 0.467 0.058 0.449 0.091
2 0 23(23) 0.379 0.105 0.640 0.029 23(23) 0.372 0.065 0.500 0.087
2 2 19(19) 0.363 0.113 0.641 0.029 11(11.1) 0.330 0.061 0.548 0.082
11 0 1360(1360) 0.246 0.109 0.559 0.033 1360(1360) 0.192 0.055 0.469 0.088
11 2 424(394.3) 0.576 0.070 0.471 0.036 195(179.3) 0.467 0.032 0.431 0.091
1,2 0 107(107) 0.450 0.104 0.701 0.026 107(107) 0.493 0.083 0.533 0.083
1,2 2 64(62.9) 0.444 0.105 0.704 0.026 33(32.1) 0.466 0.069 0.537 0.083
2,11 0 1383(1383) 0.491 0.101 0.721 0.025 1383(1383) 0.521 0.067 0.669 0.068
2,11 2 443(413.3) 0.480 0.094 0.688 0.027 206(190.4) 0.489 0.051 0.641 0.071
1,11 0 1444(1444) 0.492 0.096 0.784 0.022 1444(1444) 0.423 0.051 0.646 0.070
1,11 2 469(438.2) 0.485 0.102 0.765 0.023 217(200.3) 0.431 0.062 0.556 0.080
1,2,11 0 1467(1467) 0.518 0.098 0.767 0.023 1467(1467) 0.546 0.064 0.662 0.070
1,2,11 2 488(457.2) 0.528 0.091 0.750 0.023 228(211.4) 0.521 0.058 0.640 0.071
1,2,4,5,11 0 1523(1523) 0.523 0.099 0.760 0.023 1523(1523) 0.548 0.067 0.643 0.070
1,2,4,5,11 2 522(489.5) 0.526 0.092 0.746 0.024 244(226.8) 0.516 0.061 0.639 0.071
1,2,4,5,11,13 0 1566(1566) 0.523 0.099 0.710 0.027 1566(1566) 0.549 0.067 0.613 0.076
1,2,4,5,11,13 2 535(500.9) 0.526 0.092 0.728 0.025 249(232.7) 0.517 0.061 0.628 0.072
  1. Method numbers are from Table 1.
  2. Models trained on dataset2431 and testing performed with dataset579 and 10 × cross validation on dataset2431, features removed by increasing stringency of t-test of individual feature to activity from dataset2431.
  3. Models trained on dataset579 and testing performed with dataset2431 and 10 × cross validation on dataset579, features removed by increasing stringency of t-test of individual feature to activity from dataset579.
  4. Feature numbers in parentheses are the average number of features in cross validations.
  5. Entries in bold are column maximums from their respective tables and are provided as visual indicators. Italicized entries are column maximums within the table and are again provided as visual indicators.