Confusion matrix and data imbalances
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How do we know if a model is good or bad at classifying our data? The way that computers assess model performance sometimes can be difficult for us to comprehend or can over-simplify how the model will behave in the real world. To build models that work in a satisfactory way, we need to find intuitive ways to assess them, and understand how these metrics can bias our view.
Assess performance of classification models., Review metrics to improve classification models., Mitigate performance issues from data imbalances.
Prerequisites
Basic familiarity with classification models
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