`contrasts <-`（` * tmp * `、value = contr.funs [1 + isOF [nn]]）のエラー：対比は2つ以上のレベルの因子にのみ適用できます

Question

Rキャレットパッケージを使用してモデルを生成しています。次元削減の前処理でPCAを使用してから、ロジスティック回帰モデルを生成しようとしています。

このエラーが発生します：

contrasts<-（*tmp*、value = contr.funs [1 + isOF [nn]]）のエラー：対比は、2つ以上のレベルの因子にのみ適用できます

 credit <- read.csv('~Loans Question/RequiredAttributesWithLoanStatus.csv') credit$LoanStatus <- as.factor(credit$LoanStatus) str(credit) 'data.frame': 8580 obs. of 45 variables: $ ListingCategory : int 1 7 3 1 1 7 1 1 1 1 ... $ IncomeRange : int 3 4 6 4 4 3 3 4 3 3 ... $ StatedMonthlyIncome : num 2583 4326 10500 4167 5667 ... $ IncomeVerifiable : logi TRUE TRUE TRUE FALSE TRUE TRUE ... $ DTIwProsperLoan : num 1.8e-01 2.0e-01 1.7e-01 1.0e+06 1.8e-01 4.4e-01 2.2e-01 2.0e-01 2.0e-01 3.1e-01 ... $ EmploymentStatusDescription: Factor w/ 7 levels "Employed","Full-time",..: 1 4 1 7 1 1 1 1 1 1 ... $ Occupation : Factor w/ 65 levels "","Accountant/CPA",..: 37 37 20 14 43 58 48 37 37 37 ... $ MonthsEmployed : int 4 44 159 67 26 16 209 147 24 9 ... $ BorrowerState : Factor w/ 48 levels "AK","AL","AR",..: 22 32 5 5 14 28 4 10 10 34 ... $ BorrowerCity : Factor w/ 3089 levels "AARONSBURG","ABERDEEN",..: 1737 3059 2488 654 482 719 895 1699 2747 1903 ... $ BorrowerMetropolitanArea : Factor w/ 1 level "(Not Implemented)": 1 1 1 1 1 1 1 1 1 1 ... $ LenderIndicator : int 0 0 0 1 0 0 0 0 1 0 ... $ GroupIndicator : logi FALSE FALSE FALSE TRUE FALSE FALSE ... $ GroupName : Factor w/ 83 levels "","00 Used Car Loans",..: 1 1 1 47 1 1 1 1 1 1 ... $ ChannelCode : int 90000 90000 90000 80000 40000 40000 90000 90000 80000 90000 ... $ AmountParticipation : int 0 0 0 0 0 0 0 0 0 0 ... $ MonthlyDebt : int 247 785 1631 817 644 1524 427 817 654 749 ... $ CurrentDelinquencies : int 0 0 0 0 0 0 0 1 0 1 ... $ DelinquenciesLast7Years : int 0 10 0 0 0 0 0 0 0 0 ... $ PublicRecordsLast10Years : int 0 1 0 0 0 0 1 0 1 0 ... $ PublicRecordsLast12Months : int 0 0 0 0 0 0 0 0 0 0 ... $ FirstRecordedCreditLine : Factor w/ 4719 levels "1/1/00 0:00",..: 3032 2673 1197 2541 4698 4345 3150 925 4452 2358 ... $ CreditLinesLast7Years : int 53 30 36 26 7 22 15 20 34 32 ... $ InquiriesLast6Months : int 2 8 5 0 0 0 0 3 0 0 ... $ AmountDelinquent : int 0 0 0 0 0 0 0 63 0 15 ... $ CurrentCreditLines : int 10 10 18 10 4 11 6 10 7 8 ... $ OpenCreditLines : int 9 10 15 8 3 8 5 7 7 8 ... $ BankcardUtilization : num 0.26 0.69 0.94 0.69 0.81 0.38 0.55 0.24 0.03 0 ... $ TotalOpenRevolvingAccounts : int 9 7 12 10 3 5 4 5 4 6 ... $ InstallmentBalance : int 48648 14827 0 0 0 30916 0 21619 41340 15447 ... $ RealEstateBalance : int 0 0 577745 0 0 0 191296 0 0 126039 ... $ RevolvingBalance : int 5265 9967 94966 50511 37871 22463 19550 2436 1223 3236 ... $ RealEstatePayment : int 0 0 4159 0 0 0 1303 0 0 1279 ... $ RevolvingAvailablePercent : int 78 52 36 45 18 61 44 74 96 76 ... $ TotalInquiries : int 8 11 15 2 0 0 1 7 1 1 ... $ TotalTradeItems : int 53 30 36 26 7 22 15 20 34 32 ... $ SatisfactoryAccounts : int 52 23 36 26 7 19 15 18 34 29 ... $ NowDelinquentDerog : int 0 0 0 0 0 0 0 1 0 1 ... $ WasDelinquentDerog : int 1 7 0 0 0 3 0 1 0 2 ... $ OldestTradeOpenDate : int 5092001 5011977 12011984 4272000 9081993 9122000 6161987 11181999 9191990 4132000 ... $ DelinquenciesOver30Days : int 0 6 0 0 0 13 0 2 0 2 ... $ DelinquenciesOver60Days : int 0 4 0 0 0 0 0 0 0 1 ... $ DelinquenciesOver90Days : int 0 10 0 0 0 0 0 0 0 0 ... $ IsHomeowner : logi FALSE FALSE TRUE FALSE FALSE FALSE ... $ LoanStatus : Factor w/ 4 levels "1","2","3","4": 4 2 2 4 4 4 4 4 4 3 ... summary(credit) ListingCategory IncomeRange StatedMonthlyIncome IncomeVerifiable Min. : 0.000 Min. :1.000 Min. : 0 Mode :logical 1st Qu.: 1.000 1st Qu.:3.000 1st Qu.: 3167 FALSE:784 Median : 2.000 Median :4.000 Median : 4750 TRUE :7796 Mean : 4.997 Mean :4.089 Mean : 5755 NA's :0 3rd Qu.: 7.000 3rd Qu.:5.000 3rd Qu.: 7083 Max. :20.000 Max. :7.000 Max. :250000 DTIwProsperLoan EmploymentStatusDescription Min. : 0.0 Employed :7182 1st Qu.: 0.1 Full-time : 416 Median : 0.2 Not employed : 122 Mean : 91609.4 Other : 475 3rd Qu.: 0.3 Part-time : 7 Max. :1000000.0 Retired : 32 Self-employed: 346 Occupation MonthsEmployed BorrowerState Other :2421 Min. :-23.00 CA :1056 Professional :1040 1st Qu.: 26.00 FL : 608 Computer Programmer : 345 Median : 68.00 NY : 574 Executive : 334 Mean : 97.44 TX : 532 Administrative Assistant: 325 3rd Qu.:139.00 IL : 443 Teacher : 301 Max. :755.00 GA : 343 (Other) :3814 NA's :5 (Other):5024 BorrowerCity BorrowerMetropolitanArea LenderIndicator CHICAGO : 121 (Not Implemented):8580 Min. :0.00000 NEW YORK : 91 1st Qu.:0.00000 BROOKLYN : 88 Median :0.00000 HOUSTON : 64 Mean :0.09196 LAS VEGAS: 53 3rd Qu.:0.00000 ATLANTA : 51 Max. :1.00000 (Other) :8112 GroupIndicator GroupName Mode :logical :8326 FALSE:8325 We do not accept new membership requests: 39 TRUE :255 BORROWERS - LARGEST GROUP : 29 NA's :0 LendersClub : 17 Debt Consolidators : 12 Have Money - Will Bid : 10 (Other) : 147 ChannelCode AmountParticipation MonthlyDebt CurrentDelinquencies Min. :40000 Min. :0 Min. : 0.0 Min. : 0.0000 1st Qu.:80000 1st Qu.:0 1st Qu.: 364.0 1st Qu.: 0.0000 Median :80000 Median :0 Median : 708.0 Median : 0.0000 Mean :77196 Mean :0 Mean : 885.5 Mean : 0.4119 3rd Qu.:90000 3rd Qu.:0 3rd Qu.: 1205.2 3rd Qu.: 0.0000 Max. :90000 Max. :0 Max. :30213.0 Max. :21.0000 DelinquenciesLast7Years PublicRecordsLast10Years PublicRecordsLast12Months Min. : 0.000 Min. : 0.0000 Min. :0.00000 1st Qu.: 0.000 1st Qu.: 0.0000 1st Qu.:0.00000 Median : 0.000 Median : 0.0000 Median :0.00000 Mean : 4.009 Mean : 0.2809 Mean :0.01364 3rd Qu.: 3.000 3rd Qu.: 0.0000 3rd Qu.:0.00000 Max. :99.000 Max. :11.0000 Max. :4.00000 FirstRecordedCreditLine CreditLinesLast7Years InquiriesLast6Months 12/1/93 0:00: 20 Min. : 2.0 Min. : 0.0000 3/1/95 0:00 : 19 1st Qu.: 16.0 1st Qu.: 0.0000 6/1/90 0:00 : 17 Median : 24.0 Median : 1.0000 6/1/89 0:00 : 16 Mean : 26.1 Mean : 0.9994 12/1/90 0:00: 15 3rd Qu.: 34.0 3rd Qu.: 1.0000 2/1/94 0:00 : 14 Max. :115.0 Max. :15.0000 (Other) :8479 AmountDelinquent CurrentCreditLines OpenCreditLines BankcardUtilization Min. : 0 Min. : 0.000 Min. : 0.000 Min. :0.0000 1st Qu.: 0 1st Qu.: 5.000 1st Qu.: 5.000 1st Qu.:0.2500 Median : 0 Median : 9.000 Median : 8.000 Median :0.5400 Mean : 1195 Mean : 9.345 Mean : 8.306 Mean :0.5182 3rd Qu.: 0 3rd Qu.:12.000 3rd Qu.:11.000 3rd Qu.:0.7900 Max. :179158 Max. :54.000 Max. :42.000 Max. :2.2300 TotalOpenRevolvingAccounts InstallmentBalance RealEstateBalance Min. : 0.000 Min. : 0 Min. : 0 1st Qu.: 3.000 1st Qu.: 3338 1st Qu.: 0 Median : 6.000 Median : 14453 Median : 26154 Mean : 6.441 Mean : 24900 Mean : 109306 3rd Qu.: 9.000 3rd Qu.: 32238 3rd Qu.: 176542 Max. :44.000 Max. :739371 Max. :1938421 NA's :328 RevolvingBalance RealEstatePayment RevolvingAvailablePercent TotalInquiries Min. : 0 Min. : 0.0 Min. : 0.00 Min. : 0.00 1st Qu.: 2799 1st Qu.: 0.0 1st Qu.: 29.00 1st Qu.: 2.00 Median : 8784 Median : 346.5 Median : 52.00 Median : 3.00 Mean : 19555 Mean : 830.5 Mean : 51.46 Mean : 3.91 3rd Qu.: 21110 3rd Qu.: 1382.2 3rd Qu.: 75.00 3rd Qu.: 5.00 Max. :695648 Max. :13651.0 Max. :100.00 Max. :36.00 TotalTradeItems SatisfactoryAccounts NowDelinquentDerog WasDelinquentDerog Min. : 2.0 Min. : 1.00 Min. : 0.0000 Min. : 0.000 1st Qu.: 16.0 1st Qu.: 14.00 1st Qu.: 0.0000 1st Qu.: 0.000 Median : 24.0 Median : 21.00 Median : 0.0000 Median : 1.000 Mean : 26.1 Mean : 23.34 Mean : 0.4119 Mean : 2.343 3rd Qu.: 34.0 3rd Qu.: 30.25 3rd Qu.: 0.0000 3rd Qu.: 3.000 Max. :115.0 Max. :113.00 Max. :21.0000 Max. :32.000 OldestTradeOpenDate DelinquenciesOver30Days DelinquenciesOver60Days Min. : 1011957 Min. : 0.000 Min. : 0.000 1st Qu.: 4101996 1st Qu.: 0.000 1st Qu.: 0.000 Median : 7191993 Median : 1.000 Median : 0.000 Mean : 6934230 Mean : 4.332 Mean : 1.908 3rd Qu.:10011990 3rd Qu.: 5.000 3rd Qu.: 2.000 Max. :12312004 Max. :99.000 Max. :73.000 DelinquenciesOver90Days IsHomeowner LoanStatus Min. : 0.000 Mode :logical 1:1847 1st Qu.: 0.000 FALSE:4264 2:1262 Median : 0.000 TRUE :4316 3: 256 Mean : 4.009 NA's :0 4:5215 3rd Qu.: 3.000 Max. :99.000 try(na.fail(credit)) glmFit <- train(LoanStatus~., credit, method = "glm", family=binomial, preProcess=c("pca"), trControl = trainControl(method = "cv"))

contrasts<-（*tmp*、value = contr.funs [1 + isOF [nn]]）のエラー：対比は、2つ以上のレベルの因子にのみ適用できます

logregFit <- train(LoanStatus~., credit, method = "logreg", family=binomial, preProcess=c("pca"), trControl = trainControl(method = "cv"))

contrasts<-（*tmp*、value = contr.funs [1 + isOF [nn]]）のエラー：対比は、2つ以上のレベルの因子にのみ適用できます

howaj · Accepted Answer

エラーメッセージとデータセットの変数を見ると、変数BorrowerMetropolitanAreaのレベルは1つだけです（実際には、すべてのサンプルの値が同じである場合、予測値はまったくありません）。これが、PCAを使用してデータセットを前処理するときにcontrasts関数で問題を引き起こしていると思います。

変数trainを使用せずにデータセットでBorrowerMetropolitanArea関数を呼び出してみてください。