Can you give an example of a classifier with high bias and high variance?

Spread the Knowledge

High bias means the data is being  underfit. The decision boundary is not usually complex enough. High variance happens due to over fitting, the decision boundary is more complex than what it should be.  

High bias high variance happens when you fit a complex decision boundary that is also not fitting the training set correctly in several places. See example below :

Overfitting Model with High Variance
Complex Model as an example of Overfitting

Spread the Knowledge

Leave a Reply

Your email address will not be published. Required fields are marked *