# Int Prediction

Hi!

In my new project, I have 5 or 6 nominal attributes and I want to learn with the training example some % valorations (the training example only have ~50-60 of 100 possible % results).

I'm searching a learner to predict int (%) values. Are there any operator with that feature?

Thanks a lot.

Jorge

In my new project, I have 5 or 6 nominal attributes and I want to learn with the training example some % valorations (the training example only have ~50-60 of 100 possible % results).

I'm searching a learner to predict int (%) values. Are there any operator with that feature?

Thanks a lot.

Jorge

0

## Answers

2,531Unicornyou could transform this problem into a regression problem by changing the label into a numerical attribute. The regression learners predict a number and not a discret number of classes, so even if a value is not included, it can be returned.

Most regression learners do not cope with nominal values, so you might have to binomalise them.

Greetings,

Sebastian

19MavenBut the regression learners (as far I know) make operations with the values of the atributtes, and they give different results if the transformation to binomial values is different.

An example:

attr1: a --> 0

attr1: b --> 1

attr1: c --> 2

gives result 1

and:

attr1: a --> 2

attr1: b --> 1

attr1: c --> 0

gives result 2

And result 1, result 2 are differents

Am I wrong?

Thanks another time,

Jorge

157Mavene.g.

if attr1 can have values a, b, or c, then you create three variables:

attr1_is_a = 0/1

attr1_is_b = 0/1

attr1_is_c = 0/1

So if you have three rows, each with different values for attr1, the three new variables would take on values of:

attr1 : { attr1_is_a, attr1_is_b, attr1_is_c }

a : { 1, 0, 0 }

b : { 0, 1, 0 }

c : { 0, 0, 1 }

Hope this helps.

Keith