predict.jous {JOUSBoost} | R Documentation |
Makes a prediction on new data for a given fitted jous
model.
## S3 method for class 'jous' predict(object, X, type = c("response", "prob"), ...)
object |
An object of class |
X |
A design matrix of predictors. |
type |
The type of prediction to return. If |
... |
... |
Returns a vector of class predictions if type="response"
, or a
vector of class probabilities p(y=1|x) if type="prob"
.
## Not run: # Generate data from Friedman model # set.seed(111) dat = friedman_data(n = 500, gamma = 0.5) train_index = sample(1:500, 400) # Apply jous to adaboost classifier class_func = function(X, y) adaboost(X, y, tree_depth = 2, n_rounds = 100) pred_func = function(fit_obj, X_test) predict(fit_obj, X_test) jous_fit = jous(dat$X[train_index,], dat$y[train_index], class_func, pred_func, keep_models=TRUE) # get class prediction yhat = predict(jous_fit, dat$X[-train_index, ]) # get probability estimate phat = predict(jous_fit, dat$X[-train_index, ], type="prob") ## End(Not run)