Can anyone please tell me How to normalize rating in a scale of 1 to 5?

In Yahoo! Movies dataset user has given a rating to a movie on the scale of 1 to 13 and 0 means there is no rating to that movie.

Please tell me how to normalize it.. original rating in scale of 1 to 13 the new rating that needed in the program is 1 to 5.

  • $\begingroup$ I think your question is already answered here. $\endgroup$ – bizzinho Jun 20 '17 at 6:59

You can use the standard re-scaling formula, i.e. $value_{new} = \frac{max_{new} - min_{new}}{max_{old} - min_{old}}\times (value_{old} - max_{old}) + max_{new}$.

In your case, that would be $\frac{5-1}{13-1} \times (value_{old} - 13) + 5$. And $value_{old} = 0 = value_{new}$.

  • $\begingroup$ Usually, "a scale of 1 to 5" means the values are integral. Your solution does not produce integral values. The obvious solution is to round the results, but there are difficulties. The most problematic issue is that since $13/5$ is not integral, the number of original ratings that map to a new rating will vary between $2$ and $3$, thereby potentially creating some bias. That needs to be understood and, perhaps, controlled in some way. $\endgroup$ – whuber Jun 20 '17 at 13:50

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