我使用rpart
包来开发我的树并预测模型。最后,为了绘制ROC曲线,我尝试使用rocr
包。不使用内置数据集复制它的道歉是无法做到的。请找到我使用的csv的链接:
现在请看我的代码:
#setting up data
data<- read.csv(file.choose())
quality_binary <- ifelse(wine_quality >5,"high","low")
data <- data.frame(data,quality_binary)
#re shuffling the data
set.seed(9850)
g <- runif(nrow(data))
datar<- data[order(g),]
#removing the wine quality column since it has to be predicted
datar <- datar[-12]
library(rpart)
library(rpart.plot)
library(cvTools)
library(caret)
library(tree)
k <- 10 # setting the value for 10 fold validation
folds <- cvFolds(NROW(datar), K=k)
datar$holdoutpred <- rep(0,nrow(datar))
for(i in 1:k){
train <- datar[folds$subsets[folds$which != i], ] #training set
validation <- datar[folds$subsets[folds$which == i], ] #validation set
#tree model
tree_model_rpart_gini = rpart(quality_binary~.,data = train,
parms = list(split = "information"), method = "class")
rpart.plot(tree_model_rpart_gini,type = 3,extra = 101)
#prediction
pred_model_rpart_gini <- predict(tree_model_rpart_gini,
newdata=validation, type="class")
datar[folds$subsets[folds$which == i], ]$holdoutpred <-
pred_model_rpart_gini
}
#plotting ROC curve
library(ROCR)
pred1 <- prediction(predict(datar$pred_model_rpart_gini),
datar$quality_binary)
perf1 <- performance(pred1,"tpr","fpr")
plot(perf1)
我的错误是:
pred1 <- prediction(predict(datar$pred_model_rpart_gini),
datar$quality_binary)
Error in UseMethod("predict") :
no applicable method for 'predict' applied to an object of class "NULL"
答案 0 :(得分:0)
local function getMinutes(hours,minutes)
return (hours*60)+minutes
end
local value1 = getMinutes(time1.hours,time1.minutes)
local value2 = getMinutes(time2.hours,time2.minutes)
local currentTime = getMinutes(tonumber(os.date("%H"),tonumber(os.date("%M")))
local isBetween = false
if (currentTime >= value1 and currentTime <= value2) or (currentTime >= value2 and currentTime <= value1) then
isBetween = true
end
是datar$pred_model_rpart_gini
,即未定义。
Ou可能意味着使用NULL
(不是pred_model_rpart_gini
)代替?