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Related Questions
- Can feature permutation importance reveal which features are most closely associated with the target variable when there are many potential correlated features in the high-dimensional dataset?
- How does feature permutation importance handle feature interactions by allowing for the evaluation of complex relationships between multiple predictors and the target variable?
- In situations with numerous features and subtle nonlinear relationships, what adaptations do we need to apply for effective feature permutation importance analyses?
- Will feature permutation importance automatically prioritize the most important correlated groups of features in large data sets?
- What is the advantage of feature permutation importance to attribute the importance of multi-grouped features in conjunction versus in isolation?
- Can feature interaction analyses through permutation importance benefit greatly from dimensionality reductions?
- Which types of feature scaling in the data can possibly harm or benefit the significance measures derived from feature permutations to a certain extent
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