Patent ID: 11922279
Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 14:
15. A computer system for selecting a transformed prediction model, associated with machine learning, for estimating the uncertainty of prediction relating to a business process without using training datasets, the computer system comprising:
one or more computer processors;
one or more computer readable storage media;
program instructions stored on the one or more computer readable storage media for execution by at least one of the one or more computer processors, the program instructions comprising:
program instructions to determine a best-fit function corresponding to a prediction interval based on one or more benchmark datasets, wherein the one or more benchmark datasets is a combination of available open datasets related to a regression problem;
program instructions to calculate one or more sets of prediction interval parameters associated with the best-fit function based on training a set of regression models with the one or more benchmark datasets, further comprises:
program instructions to train the set of regression models based on a simulation approach;
program instructions to extract the one or more sets of prediction interval parameters from the set of regression models;
program instructions to normalize the one or more sets of prediction interval parameters;
program instructions to split the one or more benchmark datasets into one or more subset benchmarks datasets; and
program instructions to determine correlation between the one or more subset benchmarks dataset and the set of regression models;

program instructions to create one or more transformed predictions based on the one or more sets of parameters and based on a logical distance;
program instructions to select a transformed prediction model based on a mean absolute correlation from the one or more transformed predictions;
program instructions to update the best-fit function based on the identified one or more subset benchmark datasets and the normalized one or more sets of prediction interval parameters that are below a threshold;
program instructions to determine the selected transformed prediction model, wherein the selected transformed prediction model is used to monitor and train correlation between the prediction interval and KPIs (Key Performance Indicator) of the business process; and
program instructions to identify and remove correlations between the prediction interval and KPIs (Key Performance Indicator) that are under a threshold.