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Related Questions
- What are the common statistical tests used to compare the performance of machine learning models?
- How can I calculate the effect size to determine the practical significance of the performance difference?
- What are the assumptions required for the statistical tests, and how can I check them?
- Can I use a paired t-test to compare the performance of pre-trained and custom-trained models on the same dataset?
- What are the limitations of statistical tests in evaluating model performance, and how can I address them?
- How can I use bootstrapping or resampling to estimate the distribution of model performance metrics?
- What are some common pitfalls to avoid when interpreting the results of statistical tests for model performance comparison?
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