How would you address an imbalanced classification problem?
If the overall distribution of the outcome is heavily tilted towards one class compared to the other, the classification problem is considered to be imbalanced.
If the overall distribution of the outcome is heavily tilted towards one class compared to the other, the classification problem is considered to be imbalanced.
The F1 Score is the harmonic mean between precision and recall.
Precision measures the proportion of observations that the algorithm predicts to be positive that actually are positive labels.
One of the most useful tools for evaluating the performance of any classification algorithm is the confusion matrix.
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