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Maximize AUC

I recognize that this is a general question, but I am seeking some general guidance on approaches to consider to improve the AUC of a model. The data set I have is student data, and I need to develop a model that will predict the outcome of a student (successful/not successful). The results will be assessed by the AUC (yes, this is a course assignment). I have tried many models and many ensemble models, but am still falling short of the AUC that is set by the professor.

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AUC ROC

Accepted answers

sara20

@pb42,

Hello

AUC is an abbrevation for area under the curve. It is used in classification analysis in order to determine which of the used models predicts the classes best.

Also you can use this video.
https://academy.rapidminer.com/courses/performance-auc-demo

I hope this helps
Sara

BalazsBaranyRM

Hi!

There are many ways to get better models (which will lead to a higher AUC).

Some approaches:
- Attribute selection (remove irrelevant or noisy attributes)
- Attribute generation (sometimes the relation between attributes, their product or division or difference are also relevant indicators that help the model make better decisions)
- Downsampling the majority class if you have imbalances in the data, or weighting the minority class
- Model parameter optimization

Search for these techniques in the Academy, there are videos for all of them.

Regards,
Balázs

All comments

sara20

BalazsBaranyRM