# How to convert binominal predictions into numerical?

nudelsuppe113
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**4**Learner I
in Help

I have a Data Set with a binominal label which contains the information if a student has passed a test. I want to predict the actual points of the test by using rapidminer. After logistic regression, all I get is the binominal prediction. How can I convert this into numeric values or am I doing something wrong before?

Thx in advance

Open Spoiler:

So I have the attributes G1 and G2 both having values from 0 to 20 aka the points of the respective test. And in G3 I have just 0 and 1, is there a way to predict the points like in G1 and G2 with the help of the other attributes?

Thx in advance

Open Spoiler:

So I have the attributes G1 and G2 both having values from 0 to 20 aka the points of the respective test. And in G3 I have just 0 and 1, is there a way to predict the points like in G1 and G2 with the help of the other attributes?

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## Answers

3,483RM Data ScientistDortmund, Germany

1,635UnicornIf you really didn't want to do that for whatever reason, you could use the binominal prediction score (which should still be a number between zero and one) and then use that in a regression to predict either G1 or G2 (or combo) to calibrate your score to points, but that is definitely the long way around and potentially introduces additional error, bias, and variance to your prediction.

Lindon Ventures

Data Science Consulting from Certified RapidMiner Experts

4Learner IThanks for the answer @mschmitz!

I understand your advice but, I don't know what to do with the predicted points of G1 and G2, how can I predict G3?

Spoiler: description of the set + task

G1 and G2 are smaller tests, having no impact on the final grade (e.g. average).

My task is, to predict whether a student passes or fails G3 and how much points he reaches in that test.

So my first asumption was to predict the real number between of G3 0 and 1 and then multiply it with 20 to get the actual points. I guess that's not how it works.

I guess I'm missing something.

4Learner I3,483RM Data ScientistDortmund, Germany

4Learner Iokay but how can I predict G3 with the help of them? I mean, do I have calculate G3 with some kind of an equation depending on the weights of G1 and G2?

I can't just take the predicted points of G1 or G2 as values of G3.

Example: if a student hasn't finished G3 successfully, he must have 0-10 points. But if the predicted points of G1 or/and G2 for the same student are like 14, the value of G3 would be wrong. Do I have a mistake in reasoning here, or is there a high accurate way to calculate the points of G3?

thx in advance

1,635UnicornLindon Ventures

Data Science Consulting from Certified RapidMiner Experts