Extreme Imbalanced Data — The Worst Data Scientist Nightmare
And the Accuracy Trap
Published in
3 min readJun 17, 2022
We can say that we have imbalanced data when one of the target variable classes has a much lower frequency than the other(s). One common example is data on cancer detection. If we have 10,000 lab results to detect cancer, and we only have a relative frequency of 1% of positive results for cancer, our data is extremely…