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Version du 15 décembre 2020 à 19:10
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Confidence Interval
A confidence interval is the range of values needed to match a confidence level for estimating the features of a complete population. Confidence intervals are usually reported in the context of a margin of error, though they are two unique values. While separate, confidence intervals are closely connected to confidence levels.
The minimum confidence level is set by the machine learning human trainer, usually at 95%, though sometimes lower or higher depending on whether an unsupervised or supervised learning technique is being used.
The interval is how large a range of values you need to reach that confidence level that the sample’s results would reflect the entire population’s features.
The primary factors influencing how “tight” the confidence interval can be are the size of the sample, the confidence level, and the variability within the sample. For example, a larger and more random sample will produce a higher confidence level estimate for the total population.
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