“在重新采样的绩效指标中缺少价值”，但仅适用于庞大的数据集

Question

对于“小的”数据集，它可以正常工作。 但是，对于我最大的集合之一（n = 498.706），模型给了我错误（请参阅底部）。

有什么想法可能导致此问题？

代码片段

# Binary just the target var
predictionDB$Helpful[predictionDB$Helpful>0] <- 1

# Binary all factors
#predictionDB <- data.frame(predictionDB[1], (predictionDB[-1] > 0) * 1)


# Get rid of potentially NAs
predictionDB <- na.omit(predictionDB) # get rid of NA rows


# Split DB in Train & Test Set ( 70/30%)
trainData <- createDataPartition(y = predictionDB$Helpful, p= 0.7, list = FALSE)
trainSet <- predictionDB[trainData,]
testSet <- predictionDB[-trainData,]

# Factorizing the target variable 
trainSet[["Helpful"]] = factor(trainSet[["Helpful"]])

trctrl <- trainControl(method = "repeatedcv", 
                       number = 10, 
                       repeats = 3,
                       allowParallel = TRUE)

#parralelize SVM Code
cl <- makeCluster(detectCores()-1)        # save 1 core as spare
registerDoParallel(cl)

# machine learning code goes in here
svm_Linear <- train(Helpful ~ ., 
                    data = trainSet, 
                    method = "svmLinear",
                    trControl=trctrl,
                    preProcess = c("center", 
                                   "scale"),
                    tuneLength = 10)
stopCluster(cl)

test_pred <- predict(svm_Linear, newdata = testSet)

confusionMatrix(table(test_pred, testSet$Helpful))

警告事项

Warning in .Internal(gc(verbose, reset, full)) :
  closing unused connection 34 (<-localhost:11963)


Error:

There were missing values in resampled performance measures.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   :1     NA's   :1    
Error: Stopping

Answer 1

我想我已经找到了错误，但是我必须先看一下。

outfile = "Log.txt"到cl <- makeCluster(detectCores()-2, outfile = "Log.txt")

给了我以下提示：

Execution halted
Error in unserialize(node$con) : error reading from connection
Calls: <Anonymous> ... doTryCatch -> recvData -> recvData.SOCKnode -> unserialize
In addition: Warning messages:
1: model fit failed for Fold04.Rep2: C=1 Error : cannot allocate vector of size 23.3 Gb

2: model fit failed for Fold10.Rep3: C=1 Error : cannot allocate vector of size 23.3 Gb```

So I`ll try to add some additional RAM to my VM.

Just in case someone else will have similar issues, hope this helps.