In the learning algorithms, Bias is generally considered as errors that declare their presence due to overly assumptions. These can sometimes result in the failure of the entire model and can largely affect the accuracy also in several cases. Some experts believe these errors are essential to enable leaner’s gain knowledge from a training point of view. On the other side, Variance is another problem that comes when the learning algorithm is quite complex. Therefore a limit is to be imposed on this.
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