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Permalink Reply by Vincent Granville on August 25, 2019 at 5:11am

The grouping you are talking about is called binning. See articles on this topic: https://www.datasciencecentral.com/page/search?q=binning

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Permalink Reply by Simon Olivier Guienguere on August 26, 2019 at 1:43pm

Dear Nitish,

Data preparation appeared to be the tedious  and the most essential section in the modeling phase.

It could be time consuming if it is appropriately done. As the adage said:" Garbage In ==> Garbage Out".

However, data audit would be crucial prior to Data Prep including but not limited:

1. Pct of missing values, valid records
2. Breakdown counts of invalid values
3. Are observations duplicated?
4. How many unique values within each variables?
5. Distribution within each attributes
6. If ND (compute the mean and the sd)
7. If NND( compute the median and the iqr)
8. Detect outliers and extreme values.
9. Check association among categorical variables.
10. Correlation with the dependent variable if you are one identified.

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Permalink Reply by David Spoerl on August 27, 2019 at 4:13am

Thank you Nitish. I have been looking for something like this

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Permalink Reply by Wayne G Fischer on August 29, 2019 at 5:42am

IMHO, although it is a common in the medical journals, it is never a good practice

to "convert" ratio data (e.g., age) into ordinal data ("categories," bins).  It results in a loss

of the information inherently contained in the ratio data compared to its ordinal representation.

For instance take age: bins of 0-5 years, 6-10 years, 11-15 years, etc.  6 and 10 years old are

treated as "equal," while 5 and 6 years old are treated as "different" as 1 and 10 years old.

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