Is it better to have a large dataset or a high-quality one?

Is it better to have a large dataset or a high-quality one?

It depends on the context. High-quality data often leads to better model performance, but a large dataset can help in generalization.

Can you explain what you mean by high-quality data?

High-quality data is accurate, relevant, and representative of the problem you're trying to solve. It reduces noise and bias.

What are the risks of using a large dataset with poor quality?

Using a large dataset with poor quality can lead to misleading results, overfitting, and ultimately a model that performs poorly in real-world scenarios.

So, how do I ensure my dataset is of high quality?

You can ensure high quality by cleaning the data, validating it, and using techniques like cross-validation to assess its reliability.