from sklearn import datasets
from sklearn.model_selection import train_test_split
from sklearn.ensemble import AdaBoostClassifier
from sklearn import metrics

iris = datasets.load_iris()
X = iris.data
y = iris.target

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3)

abc = AdaBoostClassifier(n_estimators=50, learning_rate=1)
model = abc.fit(X_train, y_train)

y_pred = model.predict(X_test)
print("Accuracy:", metrics.accuracy_score(y_test, y_pred))
dbd50672abc3be8f37434f14feb3b27a7f9c406e
<mask token>

<mask token>
print('Accuracy:', metrics.accuracy_score(y_test, y_pred))

<mask token>
iris = datasets.load_iris()
X = iris.data
y = iris.target
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3)
abc = AdaBoostClassifier(n_estimators=50, learning_rate=1)
model = abc.fit(X_train, y_train)
y_pred = model.predict(X_test)
print('Accuracy:', metrics.accuracy_score(y_test, y_pred))

from sklearn import datasets
from sklearn.model_selection import train_test_split
from sklearn.ensemble import AdaBoostClassifier
from sklearn import metrics
iris = datasets.load_iris()
X = iris.data
y = iris.target
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3)
abc = AdaBoostClassifier(n_estimators=50, learning_rate=1)
model = abc.fit(X_train, y_train)
y_pred = model.predict(X_test)
print('Accuracy:', metrics.accuracy_score(y_test, y_pred))

from sklearn import datasets
from sklearn.model_selection import train_test_split
from sklearn.ensemble import AdaBoostClassifier
from sklearn import metrics

iris = datasets.load_iris()
X = iris.data
y = iris.target

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3)

abc = AdaBoostClassifier(n_estimators=50, learning_rate=1)
model = abc.fit(X_train, y_train)

y_pred = model.predict(X_test)
print("Accuracy:", metrics.accuracy_score(y_test, y_pred))