How do I choose the right classification algorithm?

How do I choose the right classification algorithm for my project?

Choosing the right classification algorithm depends on several factors, including the size of your dataset, the nature of your data, and the specific problem you're trying to solve. Can you provide more details about your project?

I have a medium-sized dataset with both numerical and categorical features.

For medium-sized datasets with mixed features, you might consider algorithms like Random Forest or Gradient Boosting. They handle both types of data well. What is the goal of your classification?

I want to predict customer churn.

In that case, Random Forest is a great choice as it can capture complex interactions in your data. Have you thought about how you'll evaluate the model's performance?

Yes, I plan to use accuracy and F1 score.

That sounds good! Accuracy gives you a general idea, while the F1 score is crucial for imbalanced datasets. Would you like tips on model evaluation?