What are the true error and the sample error?
The true error represents the probability that a randomly drawn instance from the entire distribution is misclassified while the sample error is the fraction of sample which is misclassified.
As true error represents entire population it becomes difficult to calculate hence we use sample to check our hypothesis and use evaluation methods to check it's confidence level. A sample might not be a true representation of population so the difference in results are sample error. We try different sampling methods so that there is no bias in choosing a sample like randomised and stratified sampling.
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