confusionMatrix -错误：`data`和`reference`应该是相同级别的因子
confusionMatrix -错误：`data`和`reference`应该是相同级别的因子
提问于 2020-12-07 01:54:45
创建了一个逻辑模型：
Banks_Logit<- glm(Banks$Financial.Condition ~ .,data = Banks, family="binomial")
options(scipen=999)
summary(Banks_Logit)然后：
pred <-predict(Banks_Logit,Banks)
gain <-gains(Banks$Financial.Condition,pred,groups=20)
plot(c(0,gain$cume.pct.of.total*sum(Banks$Financial.Condition))~
c(0,gain$cume.obs),
xlab = "Observations", ylab = "Cumulative", main="Model Performance", type="l")
lines(c(0,sum(Banks$Financial.Condition))~c(0,dim(Banks)[1]),lty=2)
library(caret)
confusionMatrix(ifelse(pred >0.5, 1,0), Banks$Financial.Condition)错误-错误：data和reference应该是相同级别的因子。
这是pred数据
1 2 3 4 5 6 7 8 9 10
0.9999999999999997779554 0.9999999999999997779554 0.9999999999999997779554 0.9999999999999997779554 0.9999999999999997779554 0.9999999999999997779554 0.9999999999138624584560 0.9999999999891036051025 0.9999999999995110577800 0.9999999999999997779554
11 12 13 14 15 16 17 18 19 20
0.0000000000176082421301 0.0000000000352379135751 0.0000000000431425778626 0.0000000000000002220446 0.0000000000002227450487 0.0000000000000002220446 0.0000000000000002220446 0.0000000000000002220446 0.0000000000000002220446 0.0000000000000002220446
str(pred)
Named num [1:20] 1 1 1 1 1 ...
- attr(*, "names")= chr [1:20] "1" "2" "3" "4" ...
this is the dataset (Str(Banks):
'data.frame': 20 obs. of 5 variables:
$ Obs : int 1 2 3 4 5 6 7 8 9 10 ...
$ Financial.Condition: int 1 1 1 1 1 1 1 1 1 1 ...
$ TotCap.Assets : num 9.7 1 6.9 5.8 4.3 9.1 11.9 8.1 9.3 1.1 ...
$ TotExp.Assets : num 0.12 0.11 0.09 0.1 0.11 0.13 0.1 0.13 0.16 0.16 ...
$ TotLns.Lses.Assets : num 0.65 0.62 1.02 0.67 0.69 0.74 0.79 0.63 0.72 0.57 ...回答 1
Stack Overflow用户
发布于 2020-12-11 08:27:21
下面是一些示例数据：
Banks = data.frame(Obs = 1:100,Financial.Condition=rbinom(100,1,0.5),
TotCap.Assets = runif(100),
TotExp.Assets = runif(100),TotLns.Lses.Assets = runif(100))您可以只提供confusionMatrix的表，以获取其他指标：
library(caret)
Banks_Logit<- glm(Banks$Financial.Condition ~ .,data = Banks, family="binomial")
pred <-predict(Banks_Logit,Banks)
confusionMatrix(table(ifelse(pred >0.5, 1,0), Banks$Financial.Condition))
Confusion Matrix and Statistics
0 1
0 36 33
1 8 23
Accuracy : 0.59
95% CI : (0.4871, 0.6874)
No Information Rate : 0.56
P-Value [Acc > NIR] : 0.3084356
Kappa : 0.2158
Mcnemar's Test P-Value : 0.0001781
Sensitivity : 0.8182
Specificity : 0.4107
Pos Pred Value : 0.5217
Neg Pred Value : 0.7419
Prevalence : 0.4400
Detection Rate : 0.3600
Detection Prevalence : 0.6900
Balanced Accuracy : 0.6144
'Positive' Class : 0页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/65171218
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