How does incorrect imputation of missing data influence the accuracy of a predictive model?
- Decreases accuracy.
- Depends on the specific model.
- Increases accuracy.
- No effect on accuracy.
Incorrect imputation of missing data can lead to the model learning incorrect patterns, which in turn can significantly decrease the accuracy of predictions.
Loading...
Related Quiz
- ________ is one potential cause of outliers in a dataset.
- In a positively skewed distribution, which is greater: mean or median?
- How is model-based method different from the other two imputation methods?
- What is the name of the statistical measure that shows the degree of the relationship between two variables?
- Given a set of data that follows a Binomial Distribution, how would you estimate the parameters of the distribution?