hgboost

hgboost_import_init.py

# Import the library
from hgboost import hgboost

# Initialize library.
hgb = hgboost(
    max_eval=250,      # Search space is based  on the number of evaluations.
    threshold=0.5,     # Classification threshold. In case of two-class model this is 0.5.
    cv=5,              # k-folds cross-validation.
    test_size=0.2,     # Percentage split for the testset.
    val_size=0.2,      # Percentage split for the validationset.
    top_cv_evals=10,   # Number of top best performing models that is evaluated.
    is_unbalance=True, # Control the balance of positive and negative weights, useful for unbalanced classes.
    random_state=None, # Fix the random state to create reproducible results.
    n_jobs=-1,         # The number of CPU jobs to run in parallel. -1 means using all processors.
    gpu=False,         # Compute using GPU in case of True.
    verbose=3,         # Print progress to screen.
)