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Hi everyone,
I am an academic researcher venturing into machine learning for one of my projects. I am trying to identify the gender of company executives based on their recorded voice over the phone. Here are the different datasets that I am working with:
I have tried a few different models on the training dataset, with great success. When I split the training dataset 80% 20% to run some tests, I get an accuracy of roughly 97%. When I apply the saved model to the testing dataset from the real population, accuracy drops to 85%. I am worried that this is in part due to the imbalance in gender.
What would be the best practices to tackle such problem?
Thanks a lot!
submitted by /u/newtomtl83
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