使用R中的CARET软件包，在虹膜数据上应用KNN时缺少精度值

发布于 2025-02-13 04:34:14 字数 887 浏览 1 评论 0原文

有问题；所有准确度量值都缺少：在虹膜数据上应用K-NN时会遇到此错误。 '''iris.knn＆lt; - iris

# Dividing data into test_train
set.seed(532)
sample.iris.knn <- sample.split(iris.knn, SplitRatio = 0.8)
train.iris.knn <- subset(iris.knn, sample.iris.knn== TRUE)
test.iris.knn <- subset(iris.knn, sample.iris.knn == FALSE)
dim(train.iris.knn)
str(train.iris.knn)
head(train.iris.knn)
# fitting K-nn model
set.seed(8237)
trControl.iris.knn <- trainControl(method = "repeatedcv",
                                    number = 10,
                                    repeats = 3)

iris.knn.model <- train(Species ~., data = train.iris.knn,
                        method = 'knn',
                        trainControl = trControl.iris.knn,
                        preProcess = c("center", "scale"),
                        tuneLength = 13)
# Model check
iris.knn.model

''''

原文

Something is wrong; all the Accuracy metric values are missing:
getting this error while applying k-nn on iris data.
''' iris.knn<- iris

# Dividing data into test_train
set.seed(532)
sample.iris.knn <- sample.split(iris.knn, SplitRatio = 0.8)
train.iris.knn <- subset(iris.knn, sample.iris.knn== TRUE)
test.iris.knn <- subset(iris.knn, sample.iris.knn == FALSE)
dim(train.iris.knn)
str(train.iris.knn)
head(train.iris.knn)
# fitting K-nn model
set.seed(8237)
trControl.iris.knn <- trainControl(method = "repeatedcv",
                                    number = 10,
                                    repeats = 3)

iris.knn.model <- train(Species ~., data = train.iris.knn,
                        method = 'knn',
                        trainControl = trControl.iris.knn,
                        preProcess = c("center", "scale"),
                        tuneLength = 13)
# Model check
iris.knn.model

'''

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屋檐 2025-02-20 04:34:14

函数train命名traincontrol中没有参数

iris.knn.model <- train(Species ~., data = train.iris.knn,
                        method = 'knn',
                        trControl = trControl.iris.knn,
                        preProcess = c("center", "scale"),
                        tuneLength = 13)

There is no argument in the function train named trainControl , it is trControl so change it will solve your problem

iris.knn.model <- train(Species ~., data = train.iris.knn,
                        method = 'knn',
                        trControl = trControl.iris.knn,
                        preProcess = c("center", "scale"),
                        tuneLength = 13)

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