Comparing custom GBM's log-loss to sklearn's

compare_gbm_log_loss.py

from sklearn.ensemble import GradientBoostingClassifier
from sklearn.metrics import log_loss

custom_gbm = CustomGradientBoostingClassifier(
    n_estimators=20, 
    learning_rate=0.1, 
    max_depth=1
)
custom_gbm.fit(x, y)
custom_gbm_log_loss = log_loss(y, custom_gbm.predict_proba(x))
print(f"Custom GBM Log-Loss:{custom_gbm_log_loss:.15f}")

sklearn_gbm = GradientBoostingClassifier(
    n_estimators=20, 
    learning_rate=0.1, 
    max_depth=1
)
sklearn_gbm.fit(x, y)
sklearn_gbm_log_loss = log_loss(y, sklearn_gbm.predict_proba(x))
print(f"Scikit-learn GBM Log-Loss:{sklearn_gbm_log_loss:.15f}")