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AirQo Ugandan Air Quality Forecast Challenge

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Handling missing values
Data · 21 May 2020, 13:37 · 2

Any suggestions on handling null values, there seem to be too many to replace them with mean or median or dropping the row(sample).

Discussion 2 answers

If you are using lightgbm or similar packages, I would suggest you to leave them as it is, they can handle NaN values by default, quite well. Another tip could be using a very large negative number say -99999, so that its handled it completely different from other values. You can also try to polate the values. Mean, Median Mode imputation, I would not suggest in this case.

21 May 2020, 14:00
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