What is error rate analysis and why is it important?
Error rate analysis is the process of evaluating the frequency of errors in a dataset or model. It's crucial for improving accuracy.
How do you calculate the error rate?
The error rate is calculated by dividing the number of incorrect predictions by the total number of predictions, then multiplying by 100.
What are some common methods to reduce error rates?
Common methods include data cleaning, feature selection, model tuning, and using ensemble methods to improve predictions.
Can you give an example of error rate analysis in a real-world scenario?
Sure! In healthcare, error rate analysis can be used to evaluate diagnostic tools, ensuring they provide accurate results for patient care.
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