In a machine learning project, your data is not normally distributed, which is causing problems in your model. What are some strategies you could use to address this issue?
- All of the above
- Change the type of machine learning model to one that does not assume a normal distribution
- Use data transformation techniques like logarithmic or square root transformations
- Use non-parametric statistical methods
Several strategies can be used to address non-normal data in a machine learning project: data can be transformed using methods like logarithmic or square root transformations; non-parametric statistical methods that do not assume a normal distribution can be used; or a different type of machine learning model that does not assume a normal distribution can be chosen.
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