Random Noise
A random perturbation in data whose expected value is zero. It tends to cancel out as sample size grows and has limited impact on model performance.
Timeline (last 90 days)
When the sample size is large enough, random noise tends to cancel out statistically, and the marginal benefit of cleaning diminishes as the amount of data grows.
The expectation of systematic bias is nonzero, and no amount of data can eliminate it through averaging; if the annotation team has a consistent misunderstanding of a certain type of sample, the network will learn that error as a true pattern.
All Facts (2)
When the sample size is large enough, random noise tends to cancel out statistically, and the marginal benefit of cleaning diminishes as the amount of data grows.
50%UnverifiedThe expectation of systematic bias is nonzero, and no amount of data can eliminate it through averaging; if the annotation team has a consistent misunderstanding of a certain type of sample, the network will learn that error as a true pattern.
50%