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 make_classification
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score

# Generate a random dataset
X, y = make_classification(random_state=42)

# Split the dataset into training and testing sets
X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=42)

# Create the estimators
estimators = [
    ('lr', LogisticRegression(penalty='l2')),
    ('svm', SVC()),
    ('dt', DecisionTreeClassifier())

# Create the voting classifier
voting_classifier = VotingClassifier(estimators)

# Fit the voting classifier to the training data, y_train)

# Make predictions on the testing data
y_pred = voting_classifier.predict(X_test)

# Evaluate the accuracy of the voting classifier
accuracy = accuracy_score(y_test, y_pred)
print("Accuracy:", accuracy)