What are Bias and Variance?

Bias is the difference between the average prediction of our model and the correct value. If the bias value is high, then the prediction of the model is not accurate.

Variance is the number that gives the difference of prediction over a training set and the anticipated value of other training sets. High variance may lead to large fluctuation in the output.