from
sklearn.ensemble
import
VotingClassifier
from
sklearn.linear_model
import
LogisticRegression
from
sklearn.svm
import
SVC
from
sklearn.tree
import
DecisionTreeClassifier
from
sklearn.datasets
import
load_iris
from
sklearn.metrics
import
accuracy_score
from
sklearn.model_selection
import
train_test_split
iris
=
load_iris()
X
=
iris.data[:, :
4
]
Y
=
iris.target
X_train, X_test, y_train, y_test
=
train_test_split(X,
Y,
test_size
=
0.20
,
random_state
=
42
)
estimator
=
[]
estimator.append((
'LR'
,
LogisticRegression(solver
=
'lbfgs'
,
multi_class
=
'multinomial'
,
max_iter
=
200
)))
estimator.append((
'SVC'
, SVC(gamma
=
'auto'
, probability
=
True
)))
estimator.append((
'DTC'
, DecisionTreeClassifier()))
vot_hard
=
VotingClassifier(estimators
=
estimator, voting
=
'hard'
)
vot_hard.fit(X_train, y_train)
y_pred
=
vot_hard.predict(X_test)
score
=
accuracy_score(y_test, y_pred)
print
(
"Hard Voting Score % d"
%
score)
vot_soft
=
VotingClassifier(estimators
=
estimator, voting
=
'soft'
)
vot_soft.fit(X_train, y_train)
y_pred
=
vot_soft.predict(X_test)
score
=
accuracy_score(y_test, y_pred)
print
(
"Soft Voting Score % d"
%
score)