Mishandling missing data can lead to a high level of ________, impacting model performance.
- bias
- precision
- recall
- variance
If missing data is handled improperly, it can lead to biased training data, which can cause the model to learn incorrect or irrelevant patterns and, as a result, adversely affect its performance.
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