`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

object generated by

`ada`

.newdata

new data set to predict. This data set must be
of type ‘data.frame’ and prediction data set is required
for this approach.

type

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.

n.iter

number of iterations to consider for the prediction. By default
this is iter from the

`ada`

call (n.iter< iter)...

other arguments not used by this function.

- fit
- a vector of fitted responses. Fit will be returned if type=“vector”.
- probs
- 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”.
- both
- 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’.
- F
- this is used in the multiclass case when one uses the package to perform 1 v.s. all.

`predict.rpart`

. Furthermore,
`predict.rpart`

will be invoked to handle predictions by each tree in
the ensamble.
`ada.default`

,`summary.ada`

,`print.ada`

,
`plot.ada`

,`pairs.ada`

,`update.ada`

,`addtest`