I'm happy to see you posting again, but nonetheless I would like to ask you to specify a bit more on your posts. We need context and whenever possible sample data. And if you have a sample process, that would be a great way to get the help started!

Without sample data it is hard to know for sure, but a priori it seems that a percentage or ratio should be attribute data type numeric/real and a rating should probably be converted to a numeric/integer (this may involve transformation on your part first if you have it as labeled text in the raw form).

Brian T. Lindon Ventures Data Science Consulting from Certified RapidMiner Experts

customer rating (doesn't setting the type to polynominal lead to loss of information of hierarchy?)

I would suggest that you follow a simple rule, if you can directly compare or order different values on 'bigger-smaller' scale, than it should be of a numerical type. Which is most likely the case with a rating, as one can be higher than the other. Also keep in mind that variable type matters in case the variable is a target (label), which you are trying lo predict. In case of numerical label you face regression problem, while with polynomial label it's classification problem, which means different models should be used.

% of lower status of the population (with values e.g. 12.43) proportion of non-retail business acres per town (with values e.g. 7.87) average number of rooms per house (with values e.g. 6.575) index of accessibility to highways (with values e.g. 1,2, 3, 4, 5)

## Answers

344Unicorn1,635UnicornLindon Ventures

Data Science Consulting from Certified RapidMiner Experts

291Unicorndirectly compare or orderdifferent values on 'bigger-smaller' scale, than it should be of a numerical type. Which is most likely the case with a rating, as one can be higher than the other. Also keep in mind that variable type matters in case the variable is a target (label), which you are trying lo predict. In case of numerical label you face regression problem, while with polynomial label it's classification problem, which means different models should be used.Vladimir

http://whatthefraud.wtf

12Newbie% of lower status of the population (with values e.g. 12.43)

proportion of non-retail business acres per town (with values e.g. 7.87)

average number of rooms per house (with values e.g. 6.575)

index of accessibility to highways (with values e.g. 1,2, 3, 4, 5)

Thank you!

291UnicornHere all variables are logically numerical, first three being real and last one integer.

Vladimir

http://whatthefraud.wtf