How to handle missing data machine learning - using Missing Category
How to handle missing data machine learning
#datacleaning
#featureengineering
#missingvalueanalysis
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Missing Data is something no Data scientist want to come across but there are many reasons for Data to be missing. E.g lets say the customer does not want to give data or we can say that who ever is collecting the data might have missed it or we can say in verbal communication a lot of data is missed. So in today's video we will see how we can impute the missing data using Missing category imputation . this is one of the easiest way to impute data
This particular technique introduces a new category to data , it is very very easy ,extremely useful and takes a lot less time and data analysis.
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