Techniques for generating a hierarchical model to identify a class among a plurality of classes

A non-transitory computer readable medium storing a plurality of instructions executable by one or more processors, wherein the plurality of instructions, when executed by the one or more processors, causes the one or more processors to perform processing comprising:

• associating a plurality of classes with a root node on a first layer of a tree structure representing a hierarchical classification model, the hierarchical classification model including a plurality of classification models;
• generating the tree structure for the hierarchical classification model, wherein:
• the tree structure includes leaf nodes and non-leaf nodes;
• each non-leaf node has two child nodes associated with two respective sets of classes in the plurality of classes, wherein a difference between numbers of classes in the two sets of classes is zero or one;
• each leaf node is associated with at least two but fewer than a first threshold number of classes;
• and
• each of the leaf nodes and the non-leaf nodes is associated with a classification model in the plurality of classification models of the hierarchical classification model;
• and
• training the classification model associated with each respective node in the tree structure.

A system comprising:

• one or more processors;
• and
• a memory coupled to the one or more processors, the memory storing instructions, which, when executed by the one or more processors, cause the system to:
• associate a plurality of classes with a root node on a first layer of a tree structure representing a hierarchical classification model, the hierarchical classification model including a plurality of classification models;
• generate the tree structure for the hierarchical classification model, wherein:
• the tree structure includes leaf nodes and non-leaf nodes;
• each non-leaf node has two child nodes associated with two respective sets of classes in the plurality of classes, wherein a difference between numbers of classes in the two sets of classes is zero or one;
• each leaf node is associated with at least two but fewer than a first threshold number of classes;
• and
• each of the leaf nodes and the non-leaf nodes is associated with a classification model in the plurality of classification models of the hierarchical classification model;
• and
• train the classification model associated with each respective node in the tree structure.