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在 ConfusionMatrix 中出现错误，数据和参考因素必须具有相同数量的级别。

rmachine-learningclassificationr-caret
26

我用R caret训练了一颗树模型，现在尝试生成混淆矩阵时一直出现以下错误：

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)

在生成混淆矩阵时出现了错误。这两个对象的级别是相同的。我无法弄清楚问题所在。它们的结构和级别如下。

它们应该是相同的。如果有帮助，将不胜感激，因为这让我崩溃了!!

> 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$category)
 [1] "16-Merchant Service Charge"   "17-Unpaid Cheque Fee"         "18-Gov. Stamp Duty"           "Misc"                         "26-Standard Transfer Charge" 
 [6] "29-Bank Giro Credit"          "3-Cheques Debit"              "32-Standing Order - Debit"    "33-Inter Branch Payment"      "34-International"            
[11] "35-Point of Sale"             "39-Direct Debits Received"    "4-Notified Bank Fees"         "40-Cash Lodged"               "42-International Receipts"   
[16] "46-Direct Debits Paid"        "56-Credit Card Receipts"      "57-Inter Branch"              "58-Unpaid Items"              "59-Inter Company Transfers"  
[21] "6-Notified Interest Credited" "61-Domestic"                  "64-Charge Refund"             "66-Inter Company Transfers"   "67-Suppliers"                
[26] "68-Payroll"                   "69-Domestic"                  "73-Credit Card Payments"      "82-CHAPS Fee"                 "Uncategorised"
在您的错误中，“category”被拼写为“catgeory”。如果问题与此无关，那么identical(levels(predictionsTree),levels(testdata$category))的输出是什么？ - fxi
嗨，谢谢你指出那个愚蠢的拼写错误......哎呀!!! 我运行了相同的函数并输出结果为[1] TRUE 。但是当我运行confusionMatrix函数时，现在出现以下错误.....table(data, reference, dnn = dnn, ...) :所有参数必须具有相同的长度。 - user2987739
检查是否还有拼写错误的 catgeory，检查 length(testdata$category) 和 length(predictionsTree)，同时检查两个向量的摘要。如果您只想要一个简单的混淆矩阵：table(predictionsTree,testdata$category)。 - fxi
11个回答
0

我遇到了同样的问题，我通过使用R有序因子数据类型解决了它。

levels <- levels(predictionsTree)
levels <- levels[order(levels)]    
table(ordered(predictionsTree,levels), ordered(testdata$catgeory, levels))
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