How do different machine learning models compare?

How do different machine learning models compare?

Different ML models vary in complexity, accuracy, and use cases. Are you interested in specific models?

Yes, can you compare decision trees and neural networks?

Decision trees are interpretable and work well with small datasets, while neural networks excel in handling large datasets and complex patterns.

What about their performance metrics?

Decision trees often use accuracy and F1 score, while neural networks may also consider precision, recall, and AUC-ROC.

Which one should I choose for my project?

It depends on your data size and complexity. For simpler tasks, start with decision trees; for more complex tasks, consider neural networks.