Efficient execution of a decision tree

A system comprising:

• one or more processing units;
• and
• a memory coupled to the one or more processing units and storing instructions thereon, the instructions, when executed by the one or more processing units, performing acts comprising:
• obtaining respective target values of a plurality of attributes of a target entity, the plurality of attributes being used for prediction in a decision tree;
• obtaining representations of a plurality of leaf nodes of the decision tree, each of the representations indicating respective statistic values of a plurality of attributes of historical entities and a statistic prediction result determined from historical prediction results output at a respective one of the plurality of leaf nodes for the historical entities;
• determining respective distance measures between the target entity and the plurality of leaf nodes based on the target values and the statistic values indicated by the representations of the plurality of leaf nodes;
• and
• determining a target prediction result for the target entity based on the respective distance measures and the statistic prediction results of the historical entities.

A computer program product being tangibly stored on a non-transient machine-readable medium and comprising machine-executable instructions, the instructions, when executed on a device, causing the device to perform acts comprising:

• obtaining respective target values of a plurality of attributes of a target entity, the plurality of attributes being used for prediction in a decision tree;
• obtaining representations of a plurality of leaf nodes of the decision tree, each of the representations indicating respective statistic values of a plurality of attributes of historical entities and a statistic prediction result determined from historical prediction results output at a respective one of the plurality of leaf nodes for the historical entities;
• determining respective distance measures between the target entity and the plurality of leaf nodes based on the target values and the statistic values indicated by the representations of the plurality of leaf nodes;
• and
• determining a target prediction result for the target entity based on the respective distance measures and the statistic prediction results of the historical entities.