What are the key features of scikit-learn?

What are the key features of scikit-learn?

Scikit-learn is a powerful machine learning library in Python. Its key features include a wide range of algorithms for classification, regression, clustering, and dimensionality reduction, as well as tools for model selection and evaluation.

Can you explain how to use its model selection tools?

Certainly! Scikit-learn provides tools like GridSearchCV and RandomizedSearchCV to help you find the best hyperparameters for your model. You can specify the model, the parameters to tune, and the scoring method.

What types of algorithms does it support?

Scikit-learn supports various algorithms, including linear models, decision trees, support vector machines, ensemble methods, and clustering algorithms like K-means.

Is it suitable for large datasets?

Yes, scikit-learn is designed to handle large datasets efficiently, but performance may vary depending on the algorithm and the available system resources.