How to predict a class with a rpart object?
Predicting with an rpart object also includes the parameter Type. From the help: If the rpart object is a classification tree, then the default is to return prob predictions, a matrix whose columns are the probability of the first, second, etc. class. In your case it returns the probabilities of the classes, not the class itself.
When to return ProB predictions in rpart tree?
From the help: If the rpart object is a classification tree, then the default is to return prob predictions, a matrix whose columns are the probability of the first, second, etc. class. In your case it returns the probabilities of the classes, not the class itself.
Which is the default in rpart classification tree?
If the rpart object is a classification tree, then the default is to return prob predictions, a matrix whose columns are the probability of the first, second, etc. class. In your case it returns the probabilities of the classes, not the class itself.
How does minsplit do cross validation in rpart?
The specified minsplit essentially creates a tree that categorizes each terminal node into either all “present” or all “absent”. rpart will not prune the tree for you, but can provide cross-validation for you to select the best subtree (i.e. select the complexity parameter $\\alpha$).
Which is the generic function for the class rpart?
This function is a method for the generic function predict for class “rpart”. It can be invoked by calling predict for an object of the appropriate class, or directly by calling predict.rpart regardless of the class of the object.
Which is the predict.rpart function for classification trees?
For regression trees this is the mean response at the node, for Poisson trees it is the estimated response rate, and for classification trees it is the predicted class (as a number). If type = “prob” : (for a classification tree) a matrix of class probabilities.