Feature Selection, Python, Statistical Analysis, Data Analysis.
end in a ‘fence’ that is made up of the results of step 6 and step 7. And outlier removal just means discarding all data points above and below the ‘fence’. Python has a handy function, from the numpy package called .percentile. [4] It takes an array as the first argument and the quantiles we want