predict.naiveBayes {e1071} | R Documentation |
Computes the conditional a-posterior probabilities of a categorical class variable given independent categorical predictor variables using the Bayes rule.
predict.naiveBayes(object, newdata, type = c("class", "raw"), threshold = 0.001, ...)
object |
An object of class "naiveBayes" . |
newdata |
A dataframe with new predictors. |
type |
see value. |
threshold |
Value replacing cells with 0 probabilities. |
... |
Currently not used. |
For attributes with missing values, the corresponding conditional probabilities are omitted for prediction.
If type = "raw"
, the conditional a-posterior
probabilities for each class are returned, and the class with
maximal probability else.
David Meyer david.meyer@ci.tuwien.ac.at
data(HouseVotes84) model <- naiveBayes(Class ~ ., data = HouseVotes84) predict(model, HouseVotes84[1:10,-1]) predict(model, HouseVotes84[1:10,-1], type = "raw") pred <- predict(model, HouseVotes84[,-1]) table(pred, HouseVotes84$Class) data(Titanic) m <- naiveBayes(Survived ~ ., data = Titanic) m predict(m, as.data.frame(Titanic)[,1:3])