LazyBoostingRegressor — LazyBoostingRegressor • mlsauce

Lazy Generic Boosting Regressor (AutoML Hold-out set validation)

LazyBoostingRegressor(
  verbose = 0,
  ignore_warnings = TRUE,
  custom_metric = NULL,
  predictions = FALSE,
  sort_by = "RMSE",
  random_state = 42,
  estimators = "all",
  preprocess = FALSE,
  n_jobs = NULL
)

Arguments

verbose:: int, progress bar (yes = 1) or not (no = 0) (currently).
ignore_warnings:: bool, ignore warnings.
custom_metric:: function, custom metric.
predictions:: bool, return predictions.
sort_by:: str, sort by metric.
random_state:: int, random state.
estimators:: str, estimators to use. List of names for custom, or just 'all'.
preprocess:: bool, preprocess data or not.
n_jobs:: int, number of jobs.

Value

LazyBoostingRegressor object

Examples


library(mlsauce)
library(datasets)

data(mtcars)

X <- as.matrix(mtcars[, -1])
y <- as.integer(mtcars[, 1]) 

n <- dim(X)[1]
p <- dim(X)[2]

set.seed(21341)
train_index <- sample(x = 1:n, size = floor(0.8*n), replace = TRUE)
test_index <- -train_index

X_train <- as.matrix(X[train_index, ])
y_train <- as.integer(y[train_index])
X_test <- as.matrix(X[test_index, ])
y_test <- as.integer(y[test_index])

obj <- LazyBoostingRegressor(verbose=0, ignore_warnings=TRUE,
                              custom_metric=NULL, preprocess=FALSE)

obj$fit(X_train, X_test, y_train, y_test)
#> Error in py_call_impl(callable, call_args$unnamed, call_args$named): IndexError: index 0 is out of bounds for axis 0 with size 0
#> Run `reticulate::py_last_error()` for details.