Predict a data set using Ada
predict classifies a new set of observations from a
previously built classifier. This function will provide either
a vector of new classes, class probability estimates, or both.
"predict"(object, newdata, type = c("vector", "probs", "both","F"),n.iter=NULL,...)
- object generated by
- new data set to predict. This data set must be of type data.frame and prediction data set is required for this approach.
- choice for preditions. type=vector returns the default class labels. type=prob returns the probability class estimates. type=both returns both the default class labels and probability class estimates. type=F returns the ensamble average, where the class label is sign(F). This is mainly usefull for the multiclass case.
- number of iterations to consider for the prediction. By default
this is iter from the
adacall (n.iter< iter)
- other arguments not used by this function.
This function was modeled after
predict.rpart will be invoked to handle predictions by each tree in
- a vector of fitted responses. Fit will be returned if type=vector.
- a matrix of class probability estimates. The first column corresponds to the first label in the levels of the response. The second column corresponds to the second label in the levels of the response. Probs are returned whenever type=probs.
- returns both the vector of fitted responses and class probability estimates. The first element returns the fitted responses and will be labeled as class. The second element returns the class probability estimates and will be labeled as probs.
- this is used in the multiclass case when one uses the package to perform 1 v.s. all.
This function is invoked by the
plot S3 generics invoked with an
ada object. If an error occurs in one of the above
commands then try using this command directly to track possible errors.
Also, the newdata data set must be of type data.frame when invoking