Prediction enhancement for classification models
AssigneeSap SE
InventorsGuilherme Ehrhardt S. Ferreira Costa, Jan Portisch
Life of this patent
Estimating the term…
Abstract
Systems and methods provide reception of an identifier of a machine learning classification model and a prediction generated by the machine learning classification model, identification of model configuration data associated with the machine learning classification model, modification of the prediction based on the model configuration data to generate an enhanced prediction comprising calibrated probabilities, and returning of the enhanced prediction.
Claims14
A system comprising:
- a storage device;
- and
- a processor to execute processor-executable program code stored on the storage device to cause the system to:
- receive an identifier of a machine learning classification model and a prediction generated by the machine learning classification model;
- identify model configuration data associated with the machine learning classification model;
- modify the prediction based on the model configuration data to generate an enhanced prediction comprising calibrated probabilities;
- modify the enhanced prediction based on an indication of similarities between classes of the machine learning classification model included in the model configuration data, the modification of the enhanced prediction comprising a determination, based on the similarities, of a first class of the classes associated with a highest probability and a second class associated with a highest probability of all classes which are not similar to the first class, and normalization of the probabilities associated with the second class and all classes associated with a lower probability than the second class and
- return the enhanced prediction.
A computer-implemented method comprising:
- receiving an identifier of a machine learning classification model and a prediction generated by the machine learning classification model;
- identifying model configuration data associated with the machine learning classification model;
- modifying the prediction based on the model configuration data to generate an enhanced prediction comprising calibrated probabilities;
- modifying the enhanced prediction based on an indication of similarities between classes of the machine learning classification model included in the model configuration data, the modifying of the enhanced prediction including determining, based on the similarities, of a first class of the classes associated with a highest probability and a second class associated with a highest probability of all classes which are not similar to the first class and normalizing the probabilities associated with the second class and all classes associated with a lower probability than the second class;
- and
- returning the enhanced prediction.
A non-transitory medium storing processor-executable program code, the program code executable to cause a system to:
- receive an identifier of a machine learning classification model and a prediction generated by the machine learning classification model;
- identify model configuration data associated with the identifier of the machine learning classification model, the model configuration data comprising a calibration function;
- modify the prediction based on the calibration function to generate an enhanced prediction comprising calibrated probabilities;
- modify the modified enhanced prediction based on an indication of similarities between classes of the machine learning classification model included in the model configuration data, the modifying of the modified enhanced prediction comprising a determination, based on the similarities, of a first class of the classes associated with a highest probability and a second class associated with a highest probability of all classes which are not similar to the first class, and normalization of the probabilities associated with the second class and all classes associated with a lower probability than the second class;
- and
- return the enhanced prediction.
Dependencies are inferred from the claim text.