When should I use oversampling or undersampling in my dataset?

When should I use oversampling or undersampling in my dataset?

Oversampling is useful when you have a minority class that is underrepresented, while undersampling helps when the majority class is too large.

Can you give me an example of when to use each?

Sure! Use oversampling when you have 100 instances of a minority class and 1000 of a majority class. Use undersampling if you have 1000 instances of a majority class and only 100 of a minority class.

What are some techniques for oversampling?

Common techniques include SMOTE (Synthetic Minority Over-sampling Technique) and random oversampling.

And for undersampling?

For undersampling, you can use random undersampling or techniques like Tomek links to remove noisy examples.