How can I improve my supervised learning models?

How can I improve my supervised learning models?

To improve your supervised learning models, consider techniques like feature engineering, hyperparameter tuning, and using ensemble methods.

What is feature engineering and why is it important?

Feature engineering involves creating new input features from your existing data to improve model performance. It's crucial because better features can lead to more accurate predictions.

Can you explain hyperparameter tuning?

Hyperparameter tuning is the process of optimizing the parameters that govern the training process of your model, which can significantly enhance its performance.

What are ensemble methods?

Ensemble methods combine multiple models to improve overall performance. Techniques like bagging and boosting are popular examples.

How do I know if my model is overfitting?

You can check for overfitting by comparing the performance of your model on training data versus validation data. A large gap indicates overfitting.