Very often the data we want to analyse and make
predictions with is full of black holes of missing data. What to do with that? Would you remove the entries (rows) with missing data? Would you remove the variables (predictors, columns) with missing values? Would you try to impute the missing values (to "guess" them)?
The strategy to follow depends on your (missing) data. Your data can have missing values which can be distributed at random, or not...
predictions with is full of black holes of missing data. What to do with that? Would you remove the entries (rows) with missing data? Would you remove the variables (predictors, columns) with missing values? Would you try to impute the missing values (to "guess" them)?
The strategy to follow depends on your (missing) data. Your data can have missing values which can be distributed at random, or not...
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