MITIGATING PARTIALITY IN REGRESSION MODELS
A computer device receives historical prediction data, where the historical prediction data includes historical data and corresponding predictions generated for the historical data by a regression machine learning model. The computing device identifies undesired predictions in the historical predict...
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Format | Patent |
Language | English |
Published |
12.05.2022
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Abstract | A computer device receives historical prediction data, where the historical prediction data includes historical data and corresponding predictions generated for the historical data by a regression machine learning model. The computing device identifies undesired predictions in the historical prediction data based, at least in part, on a perturbation analysis, where the perturbation analysis includes modifying an attribute of the historical data and using the regression machine learning model to generate predictions for the historical data with the modified attribute. The computing device trains a binary classification model to classify predictions as undesired, using the historical prediction data and the identified undesired predictions as training data. The computing device generates a prediction for a new data entry utilizing the regression machine learning model and the binary classification model. |
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AbstractList | A computer device receives historical prediction data, where the historical prediction data includes historical data and corresponding predictions generated for the historical data by a regression machine learning model. The computing device identifies undesired predictions in the historical prediction data based, at least in part, on a perturbation analysis, where the perturbation analysis includes modifying an attribute of the historical data and using the regression machine learning model to generate predictions for the historical data with the modified attribute. The computing device trains a binary classification model to classify predictions as undesired, using the historical prediction data and the identified undesired predictions as training data. The computing device generates a prediction for a new data entry utilizing the regression machine learning model and the binary classification model. |
Author | Bhide, Manish Anand Goyal, Prateek Chamarthy, Ravi Chandra |
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Snippet | A computer device receives historical prediction data, where the historical prediction data includes historical data and corresponding predictions generated... |
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SubjectTerms | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING HANDLING RECORD CARRIERS PHYSICS PRESENTATION OF DATA RECOGNITION OF DATA RECORD CARRIERS |
Title | MITIGATING PARTIALITY IN REGRESSION MODELS |
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