You are analyzing a dataset with a high degree of negative skewness. How might this affect your choice of machine learning model?
- It might lead to a preference for models that are based on median values.
- It might lead to a preference for models that are not sensitive to outliers.
- It might lead to a preference for models that are sensitive to outliers.
- It would not affect the choice of the machine learning model.
A high degree of negative skewness indicates the possibility of extreme values towards the negative end of the distribution. This might influence the choice of machine learning models, preferring those that are not sensitive to outliers, such as tree-based models, or those that make fewer assumptions about the data distribution.
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