How do I tune hyperparameters for different algorithms?
An example of an AI chatbot conversation about tuning hyperparameters for various algorithms.
How do I tune hyperparameters for different algorithms?
Tuning hyperparameters is crucial for optimizing algorithm performance. What specific algorithms are you working with?
I'm working with decision trees and support vector machines.
For decision trees, you can tune parameters like max_depth and min_samples_split. For SVMs, consider adjusting C and gamma. Would you like more details on any of these?
Yes, can you explain how to choose the right values for C and gamma in SVM?
Certainly! You can use techniques like grid search or random search with cross-validation to find optimal values for C and gamma. Start with a range of values and refine based on performance.
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