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I read several times which binning is helpful for reducing the noise of data. But how can we find out our data has noise? What if our data is clean and we reduce the accuracy of data?

Is there any method to measure noise of an attribute? When should we do binning?

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You can plot your datapoints and see if there are many outliers to the dataset. Making frequncy plots and heatmaps helps a lot in this case.Binning helps to remove smaller erroneous data points. There are other methods of reducing noise in a dataset like applying IQR.

If you want to reduce noise, apply Inter Quartile Range after applying binning only if you have a large dataset. : https://www.wikihow.com/Find-the-IQR

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  • $\begingroup$ How do heatmaps help to decide bin or not? $\endgroup$ – parvij Jun 22 '18 at 14:10
  • $\begingroup$ Heatmaps are made to analyze data and on the basis of that, you decide if you want to apply binning or not. $\endgroup$ – Jodh Singh Jun 25 '18 at 5:44

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