有没有办法提取数据中的哪些行满足 R 中混淆矩阵的每个象限？

Question

我正在为二分类问题（0 和 1）生成一个随机森林模型，我想提取模型的训练集和验证集的行，并查看数据的哪些行对应于每个象限我计算出的混淆矩阵。有没有办法在数据集中创建变量并将每个数据点标记为 "Predicted: 1, Actual: 1" 之类的？我想知道具体哪些数据点是假阳性。

# Create a Random Forest model with default parameters
model1 <- randomForest(failure ~ customer_count+    mfgr_yr+    age+    kva_rating+ existing_phasing+   manufacturer+   mounting+   owner_name+ secondary_nominal_voltage+  secondary_voltage_connection+   structure_mounting+ type_vl+    primary_nominal_voltage+    existing_phases+    temp70+ temp80+ temp90+ temp40+ temp30+ temp20+ humidity75+ humidity85+ humidity95+ wind6+  wind10+ wind15+ rain01+ rain07+ rain15+ percentoverloaded
,data = TrainSet, importance = TRUE, cutoff = c(.08,.92))
model1

# Predicting on train set
predTrain <- predict(model1, TrainSet, type = "class")
# Checking classification accuracy
table(predTrain, TrainSet$failure)  


# Predicting on Validation set
predValid <- predict(model1, ValidSet, type = "class")
# Checking classification accuracy
mean(predValid == ValidSet$failure)                    
table(predValid,ValidSet$failure)

这就是我设置混淆矩阵的方式。我不一定需要在数据集中有一个新变量，我只需要能够看到哪些数据行对应于每个象限。谢谢！

Answer 1

为了不过度思考一个非常简单的问题，我提出了一些非常简单的建议：

predTrain <- c(1,1,1,1,0,0,0,0)
TrainSet <- data.frame(failure=c(1,0,1,0,1,0,1,0))

which(predTrain == 1 & TrainSet == 1)
which(predTrain == 1 & TrainSet == 0)
which(predTrain == 0 & TrainSet == 1)
which(predTrain == 0 & TrainSet == 0)

或者如果你真的想要一个新专栏

# example data
predTrain <- c(1,1,1,1,0,0,0,0)
TrainSet <- data.frame(failure=c(1,0,1,0,1,0,1,0))

# building a new row in TrainSet

TrainSet$confusion <- 10 * predTrain + TrainSet$failure
print(TrainSet)

# alternatively

TrainSet$chrConfusion <- paste0(predTrain, TrainSet$failure)
print(TrainSet)

有没有办法提取数据中的哪些行满足 R 中混淆矩阵的每个象限？

Is there a way to extract which rows in your data are satisfying each quadrant of a confusion matrix in R?

r

extract

confusion-matrix