Confidence Intervals for Machine Learning

The value of a confidence interval is its ability to quantify the uncertainty of the estimate. It provides both a lower and upper bound and a likelihood. Taken as a radius measure alone, the confidence interval is often referred to as the margin of error and may be used to graphically depict the uncertainty of an estimate on graphs through the use of error bars. Often, the larger the sample from which the estimate was drawn, the more precise the estimate and the smaller (better) the confidence interval. We can also say that the CI tells us how precise our estimate is likely to be, and the margin of error is our measure of precision.