View source: R/training-params.r
training_params | R Documentation |
Class that contains the training parameters for the gbm model
training_params(
num_trees = 100,
interaction_depth = 1,
min_num_obs_in_node = 10,
shrinkage = 0.001,
bag_fraction = 0.5,
num_train = (2 * min_num_obs_in_node + 1)/bag_fraction + 1,
id = seq_len(num_train),
num_features = 1
)
num_trees |
Number of trees used in the fit. |
interaction_depth |
Maximum depth of each tree |
min_num_obs_in_node |
Minimum number of observations each node in a tree must have. |
shrinkage |
shrinkage parameter applied to each tree in the expansion. Also known as the learning rate or step-size reduction. |
bag_fraction |
fraction of independent training observations selected to create the next tree in the expansion. Introduces randomness in the model fit; if bag_fraction < 1 then running the same model twice will result in similar but different fits. |
num_train |
number of obs of data used in training the model.
This defaults to the minimum number of observations allowed -
|
id |
optional vector of integers, specifying which rows in the
data correspond to which observations. Individual observations may
have many rows of data associated with them. This defaults to
|
num_features |
number of random features/columns to use in
training model. This defaults to |
training parameters object
James Hickey
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