Logistic Regression cannot handle polynominal label.
ArsalanTahir
New Altair Community Member
Hello All,
I have used logistic regression to resolve citation classification problem but error on my label class (High, Medium, and Low), tried the "nominal to numerical" operator but still face this issue. please, help it's urgent.
I have used logistic regression to resolve citation classification problem but error on my label class (High, Medium, and Low), tried the "nominal to numerical" operator but still face this issue. please, help it's urgent.
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Best Answer
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Hi!
Nominal to numerical converts your attributes (the ones that build up the model) to numericals. That's fine.
However, the concept of logistic regression doesn't allow for predicting multiple classes. What you can do is predicting one class vs. all the others repeatedly and taking the prediction with the highest confidence.
There's a meta learner for that, it's called Polynominal by Binominal Classification. You can use it as a wrapper around the actual learner (logistic regression). The operator's help contains a tutorial process so you can see how it's done.
Regards,
Balázs1
Answers
-
Hi!
Nominal to numerical converts your attributes (the ones that build up the model) to numericals. That's fine.
However, the concept of logistic regression doesn't allow for predicting multiple classes. What you can do is predicting one class vs. all the others repeatedly and taking the prediction with the highest confidence.
There's a meta learner for that, it's called Polynominal by Binominal Classification. You can use it as a wrapper around the actual learner (logistic regression). The operator's help contains a tutorial process so you can see how it's done.
Regards,
Balázs1