What does error mean in machine learning?

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Error (training error, validation error and test error they are all related to the same dataset): in machine learning the word error means the distance between what the model says and what is real. The model estimates an aspect of the real world, and this cannot be done with perfect accuracy. The error can be made because of noise (that is natural or unexplained variation), or because there are too bias or to variances. Having the right Bias-Variance trade-off helps to reduce the error. Bias-Variance trade-off means to find the right measure of Bias and Variance in the model....
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