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[model:component] Add sampling techniques to address imbalanced dataset #4283

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Resolves #4281.

Investigating and adding sampling techniques (i.e. SMOTE, SMOTEEN, RandomUndersampling) to address the imbalanced dataset of bugs.

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Still a WIP. Metrics collected from SMOTE can be found here: metrics.log

Takeaways:

  • SMOTE increases the training time to around 2 hours (as opposed to the current 30-40 minute training time)
  • The precision and accuracy are extremely low

This is most likely due to the huge differences in the number of bugs in different products and components (1000+ vs 20), and SMOTE matches the number of bugs in each minority class to the majority class, making the ratio of synthetic data to real data very large.

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[model:component] Add sampling techniques to address the imbalanced training dataset
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