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I have a data frame in which one of my columns is the target value and there are lots of ordinal categories in columns of data frame.

I want to encode these ordinal categories in columns with this method which is proposed here

I didn't understand what I should do. Should I find the probability of each category in each column and substitute the amount of probability with the string of each category?

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    $\begingroup$ @BenReiniger: Thanks for highlighting, got deviated from the main question by looking at the answer. $\endgroup$ – Toros91 May 24 '19 at 3:20
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The paper you've linked describes a method for predicting an ordinal dependent variable, but it sounds like you're looking for a way to use ordinal independent variables. That part makes up just the first part of the paper's method, and is relatively easier. It's somewhat analogous with one-hot encoding: you have indicators $x\leq \alpha$ for each level $\alpha$ (except the maximum one).

For example, if the levels are Low, Medium, High, your new variables will be "Low" and "Low or Medium" (skipping "Low or Medium or High" since that's always true).

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