For a healthcare provider looking to predict patient readmissions, which feature selection technique would be most effective?
- Chi-square Test
- Principal Component Analysis
- Recursive Feature Elimination
- T-test
Recursive Feature Elimination (RFE) is a suitable technique for selecting features in healthcare data when predicting patient readmissions. RFE iteratively removes the least important features, helping to identify the most relevant variables for the prediction task. Principal Component Analysis, Chi-square Test, and T-test may be useful in other contexts but may not address the specific needs of predicting patient readmissions.
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