deepboost.formula {deepboost} | R Documentation |
Main function for deepboost model creation, using a formula
deepboost.formula(formula, data, instance_weights = NULL, tree_depth = 5, num_iter = 1, beta = 0, lambda = 0.05, loss_type = "l", verbose = TRUE)
formula |
A R Formula object see : ?formula |
data |
A data.frame of samples to train on |
instance_weights |
The weight of each example |
tree_depth |
maximum depth for a single decision tree in the model |
num_iter |
number of iterations = number of trees in ensemble |
beta |
regularisation for scores (L1) |
lambda |
regularisation for tree depth |
loss_type |
- "l" logistic, "e" exponential |
verbose |
- print extra data while training TRUE / FALSE |
A trained Deepbost model
deepboost.formula(y ~ ., data.frame(x1=rep(c(0,0,1,1),2),x2=rep(c(0,1,0,1),2),y=factor(rep(c(0,0,0,1),2))), num_iter=1) deepboost.formula(y ~ ., data.frame(x1=rep(c(0,0,1,1),2),x2=rep(c(0,1,0,1),2),y=factor(rep(c(0,0,0,1),2))), num_iter=2, beta=0.1, lambda=0.00125)