text_plain_output_1.png
from sklearn.ensemble  import AdaBoostClassifier, GradientBoostingClassifier

from sklearn.metrics import log_loss

(x_train.shape, y_train.shape, x_test.shape, y_test.shape)

gb = GradientBoostingClassifier(n_estimators=1000, max_depth=9, subsample=0.8, max_features='log2', min_samples_leaf=9, random_state=42)
gb.fit(x_train, y_train)

y_pred = gb.predict(x_test)

log_loss(y_test, y_pred)