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[Discussion] Roadblock in building a classification model

I’ve been working on a dataset, something that I’ve never worked on before.

I am in the process of building a classification model which can separate 2 classes using 2 continuous features & around 10-15 multiclass categorical features. The classes are heavily imbalanced (3:1 ratio) & I have over 500k observations.

I’ve tried a few methods like downsampling, class balancing along with a few algorithms like Logistic Regression, KNN, Random Forest, a few Gradient Boosting algorithms etc.. All these models are giving me poor results.

I am working locally & don’t have access to a cloud service, hence I’m not keen on using NNs or SVMs which tend to be more computationally expensive.

What else can I do?

Thanks

submitted by /u/Rockflagandeeeagle
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.