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Quantile normalization is a data handling technique that works on microarrays or small data sets. This statistical process can be used as the basis for some types of machine learning projects.
The use of quantile normalization is particularly popular in machine learning projects having to do with genomic sequencing or gene editing. For example, some companies on the forefront of genetic science use quantile normalization for RNA sequencing to come up with more sophisticated results in terms of gene editing and other procedures. The technology can also be useful in other fields and other types of machine learning where complex number systems determine what the computer “learns” or “knows.”