Options

# Int Prediction

Member Posts: 19 Maven
edited November 2018 in Help
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

• Options
RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 2,531 Unicorn
Hi Jorge,
you 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
• Options
Member Posts: 19 Maven
Thanks Sebastian,

But 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
• Options
Member Posts: 157 Maven
I think what Sebastian meant is to create binomial variables for each possible value of an attribute that is 1 (TRUE) if the attribute is that value, and 0 (FALSE) otherwise.

e.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