Which of the following statements is true regarding class imbalance?Group of answer choicesA label with class imbalance will always be challenging to model.An accuracy of 99% can be bad when there is high class imbalance.Upsampling is always better than downsampling.Class imbalance is a pretty rare problem to worry about.
Question
Which of the following statements is true regarding class imbalance?Group of answer choicesA label with class imbalance will always be challenging to model.An accuracy of 99% can be bad when there is high class imbalance.Upsampling is always better than downsampling.Class imbalance is a pretty rare problem to worry about.
Solution
The true statement regarding class imbalance is: "An accuracy of 99% can be bad when there is high class imbalance."
Here's why:
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"A label with class imbalance will always be challenging to model." - This is not always true. While class imbalance can make it more difficult to model, it does not always pose a challenge. It depends on the specific dataset and the techniques used.
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"An accuracy of 99% can be bad when there is high class imbalance." - This is true. In a highly imbalanced dataset, a model can achieve high accuracy by simply predicting the majority class. However, this model would be useless for predicting the minority class, which is often the class of interest.
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"Upsampling is always better than downsampling." - This is not always true. The choice between upsampling and downsampling depends on the specific situation. Sometimes, downsampling can be more effective, especially when the majority class is very large.
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"Class imbalance is a pretty rare problem to worry about." - This is not true. Class imbalance is a common problem in many real-world datasets.
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