55. How is an error different from a residual mistake?
A value error occurs, whereas a prediction depicts the difference between the dataset's observed and true values. On the other hand, the residual error is the difference between the observed and projected values. Because the true values are never known, we utilize the residual error to assess an algorithm's performance. Hence, we apply residuals to determine the degree of inaccuracy based on the observed data. It aids us in calculating an exact estimate of the error.
