US 11,868,329 B2
Multidimensional cube multivariate regression
Kunal Sawarkar, Franklin Park, NJ (US); and Jerome Kafrouni, New York, NY (US)
Assigned to International Business Machines Corporation, Armonk, NY (US)
Filed by International Business Machines Corporation, Armonk, NY (US)
Filed on May 20, 2022, as Appl. No. 17/664,227.
Prior Publication US 2023/0376472 A1, Nov. 23, 2023
Int. Cl. G06F 16/22 (2019.01); G06F 16/901 (2019.01)
CPC G06F 16/2264 (2019.01) [G06F 16/2246 (2019.01); G06F 16/2272 (2019.01); G06F 16/9024 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
facilitating, by one or more computer processors, compatibility between one or more multivariate regression models and a multidimensional dataset, comprising:
extracting, by one or more computer processors, a plurality of unidimensional chains from the multidimensional dataset;
double indexing, by one or more computer processors, the plurality of extracted unidimensional chains;
constructing, by one or more computer processors, a plurality of partial fit regression trees from the double indexed unidimensional chains, further comprising:
recursively partitioning, by one or more computer processors, the multidimensional dataset until identifying a partition capable of fitting within the one or more multivariate regression models;
responsive to a stop criterion, calculating, by one or more computer processors, one or more predictions utilizing the plurality of constructed partial fit regression trees; and
repopulating, by one or more computer processors, the multidimensional dataset with the one or more calculated predictions.