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I am trying to build a logistic regression model and a lot of my features have ordered categorical variables. I think dummy variable may not be useful as it treats each category with equal weightage. So, do i need to treat to ordered categorial variable like numerical ?

Thanks in advance .

SunilS
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  • This might help : [Similar Question](https://stackoverflow.com/questions/29528628/how-to-specify-a-variable-in-pandas-as-ordinal-categorical) – Sociopath Nov 19 '18 at 05:40

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Ordered categorical values are termed as "Ordinal" attribute in data mining where one value is less than or greater than another value. You can treat these values as nominal values or continuous values (numbers). Some of the pros and cons of treating them as numbers (continuous) are:

Pros:

  • This gives you a lot of flexibility in your choice of analysis and preserves the information in the ordering. More importantly to many analysts, it allows you to analyze the data easily.

Cons:

  • This approach requires the assumption that the numerical distance between each set of subsequent categories is equal. Otherwise depending on the domain you can make the interval large.
Deepak M
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