The correct answer is: C. Both A and B
Platt calibration and isotonic regression are two methods used for the calibration in supervised learning.
Platt calibration is a method that uses a logistic function to fit a probability distribution to the predicted values of a model. This can be used to improve the accuracy of the model’s predictions.
Isotonic regression is a method that fits a line to the predicted values of a model in such a way that the line is always non-decreasing. This can be used to improve the interpretability of the model’s predictions.
Both Platt calibration and isotonic regression are useful methods for improving the accuracy and interpretability of supervised learning models.
Here is a brief explanation of each option:
- A. Platt Calibration and Isotonic Regression
Platt calibration is a method that uses a logistic function to fit a probability distribution to the predicted values of a model. This can be used to improve the accuracy of the model’s predictions.
Isotonic regression is a method that fits a line to the predicted values of a model in such a way that the line is always non-decreasing. This can be used to improve the interpretability of the model’s predictions.
- B. Statistics and Informal Retrieval
Statistics is the study of the collection, organization, analysis, interpretation, presentation, and communication of data. Informal retrieval is the process of finding information without using formal methods, such as searching a database or using a search engine.
Statistics and informal retrieval are not methods used for the calibration in supervised learning.
- C. Both A and B
Both Platt calibration and isotonic regression are methods used for the calibration in supervised learning.
- D. None of these
None of the options are correct.