Adapting prediction models
AssigneeKoninklijke Philips N.V.
InventorsAki Sakari Härmä, Andrei Poliakov, Irina Fedulova
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Abstract
A method and system for modifying a prediction model. In particular, an inaccuracy of the prediction model is categorized into one of at least three categories. Different modifications are made to the prediction model depending on the category of the inaccuracy. In particular examples, an inaccuracy category defines what training data is used to modify the prediction model.
Claims16
A computed-implemented method of modifying a prediction model, wherein the prediction model is generated based on existing training data and is adapted to process input data to generate predicted answer data indicative of a predicted answer to a predetermined question concerning the input data, wherein the method comprises:
- performing a difference determination step comprising:
- receiving benchmark data, the benchmark data comprising example input data and corresponding actual answer data indicative of an actual or known answer to the predetermined question concerning the corresponding example input data;
- using the prediction model to process the example input data to generate predicted answer data indicative of a predicted answer to the predetermined question based on the example input data;
- and
- determining a difference between the actual answer data and the predicted answer data,
- categorizing an inaccuracy of the prediction model into one of at least three categories based on at least the difference between the actual answer data and the predicted answer data;
- and
- modifying the prediction model based on the category of inaccuracy of the prediction model wherein:
- the difference determination step is iteratively repeated to generate a plurality of differences between actual answer data and corresponding predicted answer data;
- and
- the step of categorizing the inaccuracy of the prediction model comprises:
- identifying a pattern in the plurality of differences, comprising identifying whether there is a step change in the differences and identifying if there is a gradual change in the differences;
- and
- categorizing the inaccuracy based on the identified pattern in the plurality of differences, wherein the inaccuracy is categorized as a sudden drift if there is a step change in the differences and is categorized as a gradual drift if there is a gradual change in the differences.
(canceled)
(canceled)
(canceled)
A system adapted for modifying a prediction model, wherein the prediction model is generated based on existing training data and is adapted to process input data to generate predicted answer data indicative of a predicted answer to a predetermined question concerning the input data, wherein the system comprises:
- a difference determination module adapted to perform a difference determination step by:
- receiving benchmark data, the benchmark data comprising example input data and corresponding actual answer data indicative of an actual or known answer to the predetermined question concerning the corresponding example input data;
- using the prediction model to process the example input data to generate predicted answer data indicative of a predicted answer to the predetermined question based on the example input data;
- and
- determining a difference between the actual answer data and the predicted answer data,
- a categorization unit adapted to categorize an inaccuracy of the prediction model into one of at least three categories based on at least the difference between the actual answer data and the predicted answer data;
- and
- a modification unit adapted to modify the prediction model based on the category of inaccuracy of the prediction model;
- wherein the difference determination module is adapted to iteratively repeat the difference determination step to thereby generate a plurality of differences between actual answer data and corresponding predicted answer data;
- and
- the categorization unit is adapted to categorize the inaccuracy of the prediction model by:
- identifying a pattern in the plurality of differences, comprising identifying whether there is a step change in the differences and identifying if there is a gradual change in the differences;
- and
- categorizing the inaccuracy based on the identified pattern in the plurality of differences, wherein the inaccuracy is categorized as a sudden drift if there is a step change in the differences and is categorized as a gradual drift if there is a gradual change in the differences.
(canceled)
Dependencies are inferred from the claim text.