def do_boost(x, y, m):
ada_boost = AdaBoost(x, y, m)
accuracy = accuracy_score(ada_boost.predict(x), y)
print("Шаг бустинга:", m)
print("Точность:", accuracy)
print()
draw_boost(x, y, ada_boost)
def draw_dependency(X, Y):
x = []
y = []
for i in range(1, 100):
x.append(i)
ada_boost = AdaBoost(X, Y, i)
y.append(accuracy_score(ada_boost.predict(X), Y))
plt.plot(x, y)
plt.show()
def adaBoost():
X, y = make_classification(n_samples=350, n_features=15, n_informative=10,
random_state=1111, n_classes=2,
class_sep=1., n_redundant=0)
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.15,
random_state=1111)
model = AdaBoost(n_estimators=10, max_tree_depth=5,
max_features=8)
model.fit(X_train, y_train)
predictions = model.predict(X_test)
print(predictions)
print(predictions.min())
print(predictions.max())
print('classification, roc auc score: %s'
% roc_auc_score(y_test, predictions))
