我有问题。我有一个数据集很多功能。当我尝试使用插入符号 R 执行我的 nnet 时，给我一个错误。如果我尝试执行一小部分功能，nnet 会收敛。
这是我的代码：
> dim(trainT)
[1] 130 3413
> nnFit <- train(target ~ ., data = trainT,
+ method = "nnet",
+ trControl = fitControl#,
+ #trControl = ctrl, metric = "ROC",
+ #verbose = TRUE#,
+ #tuneGrid = nnGrid
+ )
Something is wrong; all the Accuracy metric values are missing:
Accuracy Kappa
Min. : NA Min. : NA
1st Qu.: NA 1st Qu.: NA
Median : NA Median : NA
Mean :NaN Mean :NaN
3rd Qu.: NA 3rd Qu.: NA
Max. : NA Max. : NA
NA's :9 NA's :9
Error in train.default(x, y, weights = w, ...) : Stopping
In addition: There were 50 or more warnings (use warnings() to see the first 50)
>
> nnFit <- train(target ~ ., data = trainT[,1:100],
method = "nnet",
trControl = fitControl#,
#trControl = ctrl, metric = "ROC",
#verbose = TRUE#,
#tuneGrid = nnGrid
)
# weights: 102
initial value 65.440715
iter 10 value 34.586483
iter 20 value 25.531746
iter 30 value 22.930604
iter 40 value 22.919387
iter 50 value 20.326238
iter 60 value 20.018595
iter 70 value 5.289718
iter 80 value 0.016055
final value 0.000063
converged
# weights: 304
initial value 85.540457
iter 10 value 25.219303
iter 20 value 5.562977
iter 30 value 4.712105
iter 40 value 4.676887
iter 50 value 4.625627
iter 60 value 4.622304
iter 70 value 4.597801
iter 80 value 4.582877
iter 90 value 4.570602
iter 100 value 4.569542
final value 4.569542
stopped after 100 iterations
[...]
initial value 75.037558
iter 10 value 4.301843
iter 20 value 1.495044
iter 30 value 0.159978
iter 40 value 0.118735
iter 50 value 0.110560
iter 60 value 0.101595
iter 70 value 0.079860
iter 80 value 0.073034
iter 90 value 0.065459
iter 100 value 0.052024
final value 0.052024
stopped after 100 iterations
# weights: 506
initial value 95.448738
iter 10 value 20.859400
iter 20 value 6.493820
iter 30 value 5.597509
iter 40 value 5.516322
iter 50 value 5.510970
iter 60 value 5.510881
final value 5.510881
converged
你能帮助我吗？:)
PS：会议信息：
> sessionInfo()
R version 3.2.0 (2015-04-16)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 8 x64 (build 9200)
locale:
[1] LC_COLLATE=Italian_Italy.1252 LC_CTYPE=Italian_Italy.1252
[3] LC_MONETARY=Italian_Italy.1252 LC_NUMERIC=C
[5] LC_TIME=Italian_Italy.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] nnet_7.3-9 caret_6.0-47 ggplot2_1.0.1 lattice_0.20-31
loaded via a namespace (and not attached):
[1] Rcpp_0.11.6 magrittr_1.5 splines_3.2.0 MASS_7.3-40
[5] munsell_0.4.2 colorspace_1.2-6 foreach_1.4.2 minqa_1.2.4
[9] car_2.0-25 stringr_1.0.0 plyr_1.8.2 tools_3.2.0
[13] parallel_3.2.0 pbkrtest_0.4-2 grid_3.2.0 gtable_0.1.2
[17] nlme_3.1-120 mgcv_1.8-6 quantreg_5.11 e1071_1.6-4
[21] class_7.3-12 iterators_1.0.7 gtools_3.5.0 lme4_1.1-7
[25] digest_0.6.8 Matrix_1.2-0 nloptr_1.0.4 reshape2_1.4.1
[29] codetools_0.2-11 stringi_0.4-1 compiler_3.2.0 BradleyTerry2_1.0-6
[33] scales_0.2.4 SparseM_1.6 brglm_0.5-9 proto_0.3-10
编辑：我在我的代码中忘记了一个逗号 :( 我只是 col 并且仅用于测试。
@cyberj0g：
我试试你的建议：
1-分析我看到的摘要都是数字。
2-如果我调用警告 () 不会返回任何内容，但是如果我在完成 nnet me 之前尝试停止：
> nnFit <- train(target ~ ., data = trainT,
+ method = "nnet",
+ trControl = fitControl#,
+ #trControl = ctrl, metric = "ROC",
+ #verbose = TRUE#,
+ #tuneGrid = nnGrid
+ )
Warning messages:
1: In eval(expr, envir, enclos) :
model fit failed for Fold1.Rep1: size=1, decay=0e+00 Error in nnet.default(x, y, w, entropy = TRUE, ...) :
too many (3011) weights
2: In eval(expr, envir, enclos) :
model fit failed for Fold1.Rep1: size=3, decay=0e+00 Error in nnet.default(x, y, w, entropy = TRUE, ...) :
too many (9031) weights
3: In eval(expr, envir, enclos) :
model fit failed for Fold1.Rep1: size=5, decay=0e+00 Error in nnet.default(x, y, w, entropy = TRUE, ...) :
too many (15051) weights
4: In eval(expr, envir, enclos) :
model fit failed for Fold1.Rep1: size=1, decay=1e-01 Error in nnet.default(x, y, w, entropy = TRUE, ...) :
too many (3011) weights
5: In eval(expr, envir, enclos) :
model fit failed for Fold1.Rep1: size=3, decay=1e-01 Error in nnet.default(x, y, w, entropy = TRUE, ...) :
too many (9031) weights
3-如果我增加 cv 的数量（如果我理解你对它的理解）问题是一样的：
> fitControl <- trainControl(## 5-fold CV
+ method = "repeatedcv",
+ number = 1000,
+ ## repeated 5 times
+ repeats = 5)
> nnFit <- train(target ~ ., data = trainT,
+ method = "nnet",
+ trControl = fitControl#,
+ #trControl = ctrl, metric = "ROC",
+ #verbose = TRUE#,
+ #tuneGrid = nnGrid
+ )
There were 50 or more warnings (use warnings() to see the first 50)