Close this search box.
Not a member yet?
Join now and access exclusive content.

Variance-Bias Tradeoff

Fundamental concept in machine learning that describes the balance between a model’s ability to fit the data and its ability to generalize to new data. Variance refers to the model’s sensitivity to small fluctuations in the training data, while bias refers to the model’s tendency to make simplified assumptions about the data. Generally, there is a trade-off between reducing variance and reducing bias, and finding the right balance is crucial for the model’s performance.

Sign up for the Newsletter
Thank you for subscribing to our newsletter!