Patent ID: 11948056
Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A computer-implemented method for data-parallel ensemble training using gradient boosted trees, the computer-implemented method comprising:
training, using a machine learning device, an ensemble of trees using gradient boosted trees, the training comprising:
splitting a training dataset into a plurality of data portions;
assigning a data portion to each thread group from a plurality of thread groups;
executing a stage, in which each thread group, in parallel, trains a respective ensemble of decision trees, wherein the stage comprises:
performing, by each thread group, in parallel, machine learning operations for the respective ensemble of decision trees using the data portion assigned to each thread group respectively; and
validating, by each thread group, in parallel, the respective ensemble of decision trees using a data portion assigned to another thread group;

repeating execution of the stage until a predetermined threshold is satisfied; and

inferencing, by the machine learning device, a prediction using the ensemble of decision trees that comprises the respective ensemble of trees from each of the thread groups,
wherein a first thread group shares, with a second thread group, a reference of a first data portion that is assigned to said first thread group for the second thread group to perform validation after a first stage.