Machine Learning Resources

How to perform Standardization in case of outliers?

If outliers are detected and it is deemed appropriate to exclude them, they can be removed from the data before performing standardization. If it is preferable to retain the observations, an alternate form of standardization can be conducted in which the median of the series is subtracted from each observation (as a proxy for centering) and then dividing by the interquartile range (difference between 75th and 25th percentiles) in place of the standard deviation to complete the robust scaling process.

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