Conformal prediction for regression problems
In the preceding chapters, we investigated the numerous advantages that conformal prediction provides. These include the following:
- Validity and calibration: Conformal prediction maintains its validity and calibration, irrespective of the dataset’s size. This makes it a robust method for prediction across different dataset sizes.
- Distribution-free nature: One of the significant benefits of conformal prediction is its distribution-free nature. It makes no specific assumptions about the underlying data distribution, making it a flexible and versatile tool for many prediction problems.
- Compatibility with various predictors: Conformal prediction can seamlessly integrate with any point predictor, irrespective of its nature. This property enhances its adaptability and widens its scope of application in diverse domains.
- Non-intrusiveness: The conformal prediction framework is non-intrusive, implying that it does not interfere...
