What is Bias? How do I identify if the model is biased? How do I resolve model biasness?
Bias refers to results that are systematically off the mark. Think archery where your bow is sighted incorrectly. High bias doesn’t mean you’re shooting all over the place (that’s high variance) but may cause a perfect archer hit below the bullseye all the time.
There is bias-variance tradeoff blog in our website. Please go through that.