How can you evaluate the performance of an LDA model?
- By checking the size of the scatter matrices
- By comparing with PCA
- Using confusion matrix and ROC curves
- Using only accuracy
The performance of an LDA model can be evaluated using metrics like the "confusion matrix and ROC curves." These tools provide insights into the model's ability to classify instances correctly and its trade-off between sensitivity and specificity.
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