CPC G06V 10/7625 (2022.01) [G06V 10/87 (2022.01)] | 20 Claims |
1. A method for managing a tree-based learner, the method comprising
in an initialization phase:
training the tree-based learner with a first set of specimen data to process input data with an active model chain comprising at least a root model to generate an output, each member of the first set of specimen data having a value of each of a first set of features;
in an automated reconfiguration phase:
receiving a new set of specimen data, each member of the new set of specimen data having a value of each of a new set of features;
performing a comparison between the new set of specimen data and the first set of specimen data;
in response to the executed comparison indicating new values of a feature in the new set of specimen data, new values being values of the feature that are outside a range of, or otherwise different from, values of the said feature in the first set of specimen data, reconfiguring the tree-based learner by the addition of a new sub-model to the active model chain, the new sub-model being trained to process at least the new values of the feature.
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