"The format of predictions is incorrect"

Question

ROCR曲线的实现，kNN，K 10折交叉验证。我正在使用电离层数据集。

这里是供您参考的属性信息：

-- 34个都是连续的，如上所述 -- 根据定义，第 35 个属性是 "good" 或 "bad" 以上总结。这是一个二元分类任务。

data1<-read.csv('https://archive.ics.uci.edu/ml/machine-learning-databases/ionosphere/ionosphere.data',header = FALSE)

knn 本身有效，kNN 与 kfold 也有效。但是当我输入 ROCR 代码时，它不喜欢它。我收到错误："The format of predictions is incorrect"。我检查了数据帧 pred 和 Class 1。尺寸相同。我尝试使用 data.test$V35 而不是 Class1 我在使用此选项时遇到了同样的错误。

 install.packages("class")
    library(class)

nrFolds <- 10
data1[,35]<-as.numeric(data1[,35])

# generate array containing fold-number for each sample (row)
folds <- rep_len(1:nrFolds, nrow(data1))


# actual cross validation
for(k in 1:nrFolds) {
  # actual split of the data
  fold <- which(folds == k)
  data.train <- data1[-fold,]
  data.test <- data1[fold,]

  Class<-data.train[,35]
  Class1<-data.test[,35]
  # train and test your model with data.train and data.test

  pred<-knn(data.train, data.test, Class, k = 5, l = 0, prob = FALSE, use.all = TRUE)
  data<-data.frame('predict'=pred, 'actual'=Class1)
  count<-nrow(data[data$predict==data$actual,])
  total<-nrow(data.test)
  avg = (count*100)/total
  avg =format(round(avg, 2), nsmall = 2)
  method<-"KNN" 
  accuracy<-avg
  cat("Method = ", method,", accuracy= ", accuracy,"\n")
}

install.packages("ROCR")
library(ROCR)
rocrPred=prediction(pred, Class1, NULL)
rocrPerf=performance(rocrPred, 'tpr', 'fpr')
plot(rocrPerf, colorize=TRUE, text.adj=c(-.2,1.7))

感谢任何帮助。

Answer 1

这对我有用..

install.packages("class")
library(class)
library(ROCR)
nrFolds <- 10
data1[,35]<-as.numeric(data1[,35])

# generate array containing fold-number for each sample (row)
folds <- rep_len(1:nrFolds, nrow(data1))


# actual cross validation
for(k in 1:nrFolds) {
  # actual split of the data
  fold <- which(folds == k)
  data.train <- data1[-fold,]
  data.test <- data1[fold,]

  Class<-data.train[,35]
  Class1<-data.test[,35]
  # train and test your model with data.train and data.test

  pred<-knn(data.train, data.test, Class, k = 5, l = 0, prob = FALSE, use.all = TRUE)
  data<-data.frame('predict'=pred, 'actual'=Class1)
  count<-nrow(data[data$predict==data$actual,])
  total<-nrow(data.test)
  avg = (count*100)/total
  avg =format(round(avg, 2), nsmall = 2)
  method<-"KNN" 
  accuracy<-avg
  cat("Method = ", method,", accuracy= ", accuracy,"\n")

  pred <- prediction(Class1,pred)
  perf <- performance(pred, "tpr", "fpr")
  plot(perf, colorize=T, add=TRUE)
  abline(0,1)
}

"The format of predictions is incorrect"

"The format of predictions is incorrect"

r

compiler-errors

prediction

fold

knn