CODEWITHSUNDEEP
r
willow
willow

Reputation: 11

NA of pred values in a trained model in R (Caret)

set.seed(2)
rpcv <- trainControl(method='repeatedcv', number=4, repeats = 10,
                     savePredictions = T, classProbs = T)

iris2 <- iris[c(1:3,60:72,100:109),]

iris2_train <- iris2[-1,]
iris2_test <- iris2[1,]

set.seed(4)
iris_svm <- train(as.factor(Species)~., data=iris2_train, method='svmRadial', trControl=rpcv)

iris_svm$pred

If you look at iris$pred, you can see that there is an NA value. What's the problem?

Upvotes: 1

Views: 30

Answers (1)

Mohamed Desouky
Mohamed Desouky

Reputation: 4425

I think your train data set have small number of sample class setosa (just 2 samples) which too small , so run models with a large enough n and class balance

so try this

library(caret)

set.seed(2)
rpcv <- trainControl(method='repeatedcv', number=4, repeats = 10,
                     savePredictions = T, classProbs = T)

# here i increased the sample of class setosa
iris2 <- iris[c(1:10,60:72,100:109),]

iris2_train <- iris2[-1,]
iris2_test <- iris2[1,]

set.seed(4)
iris_svm <- train(as.factor(Species)~., data=iris2_train, method='svmRadial', trControl=rpcv)

iris_svm$pred

Upvotes: 0

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