ConfusionMatrix 中的错误数据和参考因素必须具有相同的级别数 [英] Error in ConfusionMatrix the data and reference factors must have the same number of levels

问题描述

我用 R 插入符训练了一个树模型.我现在正在尝试生成一个混淆矩阵并不断收到以下错误:

I've trained a tree model with R caret. I'm now trying to generate a confusion matrix and keep getting the following error:

confusionMatrix.default(predictionsTree, testdata$catgeory) 中的错误: 数据和参考因子必须具有相同的水平数

Error in confusionMatrix.default(predictionsTree, testdata$catgeory) : the data and reference factors must have the same number of levels

prob <- 0.5 #Specify class split
singleSplit <- createDataPartition(modellingData2$category, p=prob,
                                   times=1, list=FALSE)
cvControl <- trainControl(method="repeatedcv", number=10, repeats=5)
traindata <- modellingData2[singleSplit,]
testdata <- modellingData2[-singleSplit,]
treeFit <- train(traindata$category~., data=traindata,
                 trControl=cvControl, method="rpart", tuneLength=10)
predictionsTree <- predict(treeFit, testdata)
confusionMatrix(predictionsTree, testdata$catgeory)

生成混淆矩阵时出现错误.两个对象的级别相同.我无法弄清楚问题是什么.它们的结构和层次如下.他们应该是一样的.任何帮助将不胜感激，因为它让我崩溃了！！

The error occurs when generating the confusion matrix. The levels are the same on both objects. I cant figure out what the problem is. Their structure and levels are given below. They should be the same. Any help would be greatly appreciated as its making me cracked!!

> str(predictionsTree)
 Factor w/ 30 levels "16-Merchant Service Charge",..: 28 22 22 22 22 6 6 6 6 6 ...
> str(testdata$category)
 Factor w/ 30 levels "16-Merchant Service Charge",..: 30 30 7 7 7 7 7 30 7 7 ...

> levels(predictionsTree)
 [1] "16-Merchant Service Charge"   "17-Unpaid Cheque Fee"         "18-Gov. Stamp Duty"           "Misc"                         "26-Standard Transfer Charge" 
 [6] "29-Bank Giro Credit"          "3-Cheques Debit"              "32-Standing Order - Debit"    "33-Inter Branch Payment"      "34-International"            
[11] "35-Point of Sale"             "39-Direct Debits Received"    "4-Notified Bank Fees"         "40-Cash Lodged"               "42-International Receipts"   
[16] "46-Direct Debits Paid"        "56-Credit Card Receipts"      "57-Inter Branch"              "58-Unpaid Items"              "59-Inter Company Transfers"  
[21] "6-Notified Interest Credited" "61-Domestic"                  "64-Charge Refund"             "66-Inter Company Transfers"   "67-Suppliers"                
[26] "68-Payroll"                   "69-Domestic"                  "73-Credit Card Payments"      "82-CHAPS Fee"                 "Uncategorised"   

> levels(testdata$category)
 [1] "16-Merchant Service Charge"   "17-Unpaid Cheque Fee"         "18-Gov. Stamp Duty"           "Misc"                         "26-Standard Transfer Charge" 
 [6] "29-Bank Giro Credit"          "3-Cheques Debit"              "32-Standing Order - Debit"    "33-Inter Branch Payment"      "34-International"            
[11] "35-Point of Sale"             "39-Direct Debits Received"    "4-Notified Bank Fees"         "40-Cash Lodged"               "42-International Receipts"   
[16] "46-Direct Debits Paid"        "56-Credit Card Receipts"      "57-Inter Branch"              "58-Unpaid Items"              "59-Inter Company Transfers"  
[21] "6-Notified Interest Credited" "61-Domestic"                  "64-Charge Refund"             "66-Inter Company Transfers"   "67-Suppliers"                
[26] "68-Payroll"                   "69-Domestic"                  "73-Credit Card Payments"      "82-CHAPS Fee"                 "Uncategorised"       

推荐答案

尝试使用:

confusionMatrix(table(Argument 1, Argument 2)) 

这对我有用.

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