US 12,462,201 B2
Dynamically optimizing decision tree inferences
Jan Van Lunteren, Rüschlikon (CH); Nikolaos Papandreou, Thalwil (CH); Charalampos Pozidis, Thalwil (CH); Martin Petermann, Zürich (CH); Thomas Parnell, Zürich (CH); and Milos Stanisavljevic, Adliswil (CH)
Assigned to International Business Machines Corporation, Armonk, NY (US)
Filed by INTERNATIONAL BUSINESS MACHINES CORPORATION, Armonk, NY (US)
Filed on Apr. 12, 2022, as Appl. No. 17/658,841.
Prior Publication US 2023/0325681 A1, Oct. 12, 2023
Int. Cl. G06N 20/20 (2019.01); G06N 5/01 (2023.01)
CPC G06N 20/20 (2019.01) [G06N 5/01 (2023.01)] 25 Claims
OG exemplary drawing
 
1. A method of dynamically optimizing decision tree inference operations performed by a computerized system, the method comprising, at the computerized system,
repeatedly executing one or more decision trees for inference purposes and repeatedly performing an optimization procedure according to two-phase cycles, wherein
each of the cycles includes two alternating phases, the two alternating phases including a first phase and a second phase,
the one or more decision trees are executed based on a reference data structure, whereby attributes of nodes of the one or more decision trees are repeatedly accessed from the reference data structure during the first phase of each of the cycles, and
performing the optimization procedure comprises:
during the first phase of each of the cycles, monitoring the accessed attributes to update statistical characteristics of the nodes;
during the second phase of each of the cycles, configuring a substitute data structure based on the updated statistical characteristics; and
updating the reference data structure in accordance with the substitute data structure.