Low bias是什麼意思

"Low bias" is a term used in statistics and machine learning to describe a model or algorithm that has a low tendency to underrepresent the true relationship between variables in the population. In other words, a low bias model is one that is less likely to make systematic errors or underestimate the true relationship between the predictors and the outcome.

Bias is a type of error in statistical models that occurs when the model's predictions or estimates are systematically different from the true values of the population. Bias can lead to incorrect conclusions and poor decision-making. Low bias is desirable in models because it means that the model is capturing the true relationship between the variables more accurately.

However, it's important to note that low bias does not necessarily mean that a model is perfect. Models can also have high variance, which means that they may overfit the data and not generalize well to new data. Balancing bias and variance is a key challenge in model building, and techniques such as cross-validation and regularization are used to help achieve this balance.