create_classifier: Create a NGBoostClassifier object

In acca3003/ngboostR: R Wrapper for NGBoost python module

Description

Create a NGBoostClassifier object

Usage

create_classifier(
  Base = DecisionTreeRegressor(),
  Dist = Bernoulli(),
  col_sample = 1,
  learning_rate = 0.01,
  minibatch_frac = 1,
  n_estimators = as.integer(500),
  natural_gradient = TRUE,
  random_state = NULL,
  tol = 1e-04,
  verbose = TRUE,
  verbose_eval = as.integer(100)
)

Arguments

Dist	Distribution should be used
col_sample	the percent subsample of columns to use in each boosting iteration
learning_rate	the learning rate
minibatch_frac	the percent subsample of rows to use in each boosting iteration
n_estimators	the number of boosting iterations to fit
natural_gradient	logical flag indicating whether the natural gradient should be used
tol	numerical tolerance to be used in optimization
verbose	flag indicating whether output should be printed during fitting
verbose_eval	increment (in boosting iterations) at which output should be printed

Value

A NGBoostRegressor object

acca3003/ngboostR documentation built on Dec. 18, 2021, 10:21 p.m.