使用自适应重采样(CARET包)时出错

时间:2014-09-03 23:54:55

标签: r r-caret

代码:

library(caret)
#adaptative control resampling method for fitting svr
ctrlada <- trainControl(method = "adaptive_cv", number = 10, returnResamp = "final",
                     adaptive = list(min = 5,
                                     alpha = 0.05,
                                     method = "gls",
                                     complete = TRUE),
                     allowParallel = TRUE) #10 separate 10-fold cross-validations are used as the resampling scheme

set.seed(100)
marsFitacv <- train(R ~ ., data = trainSet,
                    method = "earth",
                    tuneGrid = expand.grid(degree = 2, nprune = 40:80),
                    trControl = ctrlada)

错误:

x parameter filtering failed
Error in `$<-.data.frame`(`*tmp*`, "nprune", value = NA) : 
  replacement has 1 row, data has 0

数据:

dput(head(trainSet))
structure(list(fy = c(317.913756282, 365.006253069, 392.548100067, 
305.350697829, 404.999341917, 326.558279739), fu = c(538.962896683, 
484.423120589, 607.974981919, 566.461909098, 580.287855801, 454.178316794
), E = c(194617.707566, 181322.455065, 206661.286272, 182492.029532, 
189867.929239, 181991.379749), eu = c(0.153782620813, 0.208857408687, 
0.29933255604, 0.277013319499, 0.251278125174, 0.20012525805), 
    imp_local = c(1555.3450957, 1595.41614044, 763.56392418, 
    1716.78277731, 1045.72429616, 802.742305814), imp_global = c(594.038972858, 
    1359.48216529, 1018.89209367, 850.887850177, 1381.3557372, 
    1714.66351462), teta1c = c(0.033375064111, 0.021482368218, 
    0.020905367537, 0.006956337817, 0.034913536977, 0.03009770223
    ), k1c = c(4000921.55552, 4499908.41979, 9764999.26902, 9273400.46159, 
    6163057.88855, 12338543.5703), k2_2L = c(98633499.5682, 53562216.5496, 
    51597126.6866, 79496746.0098, 54060378.6334, 88854286.5457
    ), k2_3L = c(53752551.0262, 125020222.794, 124021434.482, 
    125817803.431, 75021821.6702, 35160224.288), k2_4L = c(56725106.5978, 
    126865701.893, 145764489.664, 64837586.8755, 49128911.0832, 
    70088564.0166), bmaxc = c(3481281.32908, 4393584.00639, 2614830.02391, 
    3128593.72039, 3179348.29527, 4274637.35956), dfactorc = c(2.5474729895, 
    2.94296926288, 2.79505551368, 2.47882735165, 2.46407943564, 
    1.41121223341), amaxc = c(73832.9746763, 99150.5068997, 77165.4338508, 
    128546.996471, 53819.0447533, 54870.9707106), teta1s = c(0.015467320192, 
    0.013675755546, 0.031668366149, 0.028898297322, 0.019211801086, 
    0.013349768955), k1s = c(5049506.54552, 11250622.6842, 13852560.5089, 
    18813117.5726, 18362782.7372, 14720875.0829), k2_ab1s = c(276542468.441, 
    275768806.723, 211613299.608, 264475187.749, 162043062.526, 
    252936228.465), k2_ab2s = c(108971516.033, 114017918.32, 
    248886114.151, 213529935.615, 236891513.077, 142986118.909
    ), k2_ab3s = c(33306211.9166, 28220338.4744, 40462423.2281, 
    23450400.4429, 46044346.1128, 23695405.2598), bmaxab1 = c(4763935.86742, 
    4297372.01966, 3752983.00638, 4861240.46459, 4269771.8481, 
    4162098.23435), bmaxab2 = c(1864128.647, 1789714.6047, 2838412.50704, 
    2122535.96812, 2512362.60884, 1176995.61871), ab1 = c(66.4926766666, 
    42.7771212442, 45.4212664748, 50.3764074404, 35.4792060556, 
    34.1116517971), ab2 = c(21.0285105309, 23.5869838719, 18.8524808986, 
    10.1121885612, 10.9695055644, 12.1154127169), dfactors = c(2.47803921947, 
    0.874644748155, 0.749837099991, 1.96711589185, 2.5407774352, 
    1.28554379333), teta1f = c(0.037308451805, 0.035718600749, 
    0.012495093438, 0.000815957999, 0.002155991091, 0.02579104469
    ), k1f = c(14790480.9871, 17223538.1853, 19930679.8931, 3524230.46974, 
    15721827.0137, 13599317.0371), k2f = c(55614283.976, 54695745.7762, 
    86690362.7036, 99857853.7312, 63119072.711, 37510791.5472
    ), bmaxf = c(2094770.19484, 3633133.51482, 1361188.05421, 
    2001027.51219, 2534273.6726, 3765850.14143), dfactorf = c(0.745459795314, 
    2.04869176933, 0.853221909609, 1.76652410119, 0.523675021418, 
    1.0808768613), k2b = c(1956.92858062, 1400.78738327, 1771.23607857, 
    1104.05501369, 1756.6767193, 1509.9294956), amaxb = c(38588.0915097, 
    35158.1672213, 25711.062782, 21103.1603387, 27230.6973685, 
    43720.3558889999), dfactorb = c(0.822346959126, 2.34421354848, 
    0.79990635332, 2.99070447299, 1.76373031599, 1.38640223249
    ), roti = c(16.1560390049, 12.7223971386, 6.43238062144, 
    15.882552267, 16.0836252663, 18.2734832893), rotmaxbp = c(0.235615453341, 
    0.343204895932, 0.370304533553, 0.488746319999, 0.176135112774, 
    0.46921999001), R = c(0.022186087, 0.023768855, 0.023911029, 
    0.023935705, 0.023655335, 0.022402726)), .Names = c("fy", 
"fu", "E", "eu", "imp_local", "imp_global", "teta1c", "k1c", 
"k2_2L", "k2_3L", "k2_4L", "bmaxc", "dfactorc", "amaxc", "teta1s", 
"k1s", "k2_ab1s", "k2_ab2s", "k2_ab3s", "bmaxab1", "bmaxab2", 
"ab1", "ab2", "dfactors", "teta1f", "k1f", "k2f", "bmaxf", "dfactorf", 
"k2b", "amaxb", "dfactorb", "roti", "rotmaxbp", "R"), row.names = c(7L, 
8L, 20L, 23L, 28L, 29L), class = "data.frame")

数据没有相等的行或NaN

0 个答案:

没有答案