Question

我有一个问题。我的数据集有很多功能。当我尝试用插入符号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，那么nnet就会收敛。

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

你能帮帮我吗？：）

PS：会话信息：

> 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:(我只有col而且仅用于测试。

@ cyberj0g：

我尝试了你的建议：

1-分析我看到的摘要都是数字。

2-如果我打电话警告（）不会返回任何内容，但如果我在完成nnet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-如果我增加了cv的数量（如果我理解你很好的话），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)

Answer 1

不清楚导致错误的原因，但我建议遵循：

检查您的数据是否有异常：summary(trainT)
检查错误后的警告：warnings()
尝试增加迭代次数：trainControl(number=1000)

此外，您的完整数据集仅包含足够的样本来训练具有130个预测变量的模型（但这取决于）。仅100个样本的收敛很可能意味着什么。

R：caret和nnet大数据错误

1 个答案: