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I am trying to implement a feature into my machine learning model in which an entry feature is ranked in terms of other entry features.

So normally I would just have the feature ranked (1st...2nd....3rd) however its important to know how far each ranking is in relation to the other entries.

Student A Scores 100%
Student B Scores 85%
Student C Scores 50%
Student D scores 10%

For example, I have 4 separate entries above. So in my model instead of entering 10% for the last row as a feature for my model I would like some sort of mathematical or machine learning approach to enter a value that would show how far that 10% is in actuality from all the other 3 entries as a whole.

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    $\begingroup$ It sounds like you want to normalise the feature based on its range. Since your feature already is a percentage value ranging from 0 to 100 it already does what you need. Can you explain why 10% which is a fifth of 50% and this way representing the distance is not sufficient for your purposes? $\endgroup$ – Gegenwind Mar 24 '18 at 16:41

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