How would you handle an imbalanced dataset?

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An imbalanced dataset is when you have, for example, a classification test and 90% of the data is in one class. That leads to problems: an accuracy of 90% can be skewed if you have no predictive power on the other category of data! Here are a few tactics to get over the hump:

  1. Collect more data to even the imbalances in the dataset.
  2. Resample the dataset to correct for imbalances.
  3. Try a different algorithm altogether on your dataset.