What are the effects of noise on machine learning models?

What are the effects of noise on machine learning models?

Noise can significantly impact the performance of machine learning models by introducing errors in the data.

How does noise affect model accuracy?

Increased noise can lead to lower accuracy as the model may learn from incorrect patterns.

Can noise be mitigated in training data?

Yes, techniques like data cleaning, augmentation, and using robust algorithms can help mitigate noise.

What types of noise are most common in datasets?

Common types include random noise, outliers, and label noise, each affecting models differently.

Are there specific models that are more resilient to noise?

Yes, models like decision trees and ensemble methods tend to be more resilient to noise.