What are some advanced techniques in Scikit-learn?

What are some advanced techniques in Scikit-learn?

Scikit-learn offers several advanced techniques, such as ensemble methods, feature selection, and hyperparameter tuning. Would you like to explore any specific technique?

Can you explain ensemble methods?

Ensemble methods combine multiple models to improve performance. Techniques like bagging, boosting, and stacking are popular. Would you like to know how to implement one of these?

Yes, how do I implement Random Forest using Scikit-learn?

To implement Random Forest, you can use the RandomForestClassifier or RandomForestRegressor classes. First, import the class, then create an instance and fit it to your data. Would you like a code example?

Yes, please provide a code example.

Here's a simple example:

from sklearn.ensemble import RandomForestClassifier

# Create a Random Forest Classifier
model = RandomForestClassifier(n_estimators=100)

# Fit the model
model.fit(X_train, y_train)

This will train the model on your training data.