1. R

    How to view the resulting tree using the bagging function in R?

    I constructed a tree with the `rpart` function. Then I can plot it to look at the tree visually and also look at what % of the observations were classified correctly using `table(predict(...), ...)`. mytree=rpart(y~x1+x2+x3+x4, method="class") plot(mytree) text(mytree)...
  2. R

    rpart function: how to know the % of correct classification at every terminal node?

    I have a dataset with 277 observations.I have binary response variables i.e, 0 indicates no disease, and 1 indicates disease. I know that 180 of the observations have no disease and the 97 have the disease. I build a model and construct a classification tree to see how well my model correctly...
  3. O

    How to deal with a categorical response and continuous and categorical predictors?

    Hi all, I have a large dataset of categorical and continuous variables, the observations are animal species. I want to test which variables are more influent in determining a categorical variables with 3 levels. So I have a categorical response variable (3 levels) and many possible predictors...