Ordinal classification packages and algorithms

user_185175 0
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I'm attempting to make a classifier that chooses a rating (1-5) for a item i. For each item i, I have a vector x containing about 40 different quantities pertaining to i. I also have a gold standard rating for each item. Based on some function of x, I want to train a classifier to give me a rating 1-5 that closely matches the gold standard.

Most of the information I've seen on classifiers deal with just binary decisions, while I have a rating decision. Are there common techniques or code libraries out there to deal with this sort of problem?

classification machine-learning
6 Answers

There are two packages in R that might help taming ordinal data

  1. ordinalForest on CRAN
  2. rpartScore on CRAN
user_3194870

I'm working on an OrdinalClassifier that is based on the sklearn framework (specifically the OVR multiclass classifier) and which works well with sklearn workflow such as pipelines, cross validation, and scoring.

Through testing, I'm finding that it performs very well vs. standard non-ordinal multiclass classification using SVC. And it gives much greater control over optimizing for precision and recall on the positive class (in my testing, I used sklearn's diabetes dataset and transformed the disease progression target(y) into a low, medium, high class label. Testing via cross validation is on my repo along with attribution. Scoring is based on weighted f1.

https://github.com/leeprevost/OrdinalClassifier

user_73971950
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