View source for US Patent Application 18044503. SECRET DECISION TREE TEST APPARATUS, SECRET DECISION TREE TEST SYSTEM, SECRET DECISION TREE TEST METHOD, AND PROGRAM simplified abstract

=SECRET DECISION TREE TEST APPARATUS, SECRET DECISION TREE TEST SYSTEM, SECRET DECISION TREE TEST METHOD, AND PROGRAM=


==Organization Name==

[[NIPPON TELEGRAPH AND TELEPHONE CORPORATION]]


==Inventor(s)==

[[Koki Hamada of Tokyo (JP)]]


==SECRET DECISION TREE TEST APPARATUS, SECRET DECISION TREE TEST SYSTEM, SECRET DECISION TREE TEST METHOD, AND PROGRAM - A simplified explanation of the abstract==


*This abstract for appeared for US patent application  number 18044503 Titled 'SECRET DECISION TREE TEST APPARATUS, SECRET DECISION TREE TEST SYSTEM, SECRET DECISION TREE TEST METHOD, AND PROGRAM'

==Simplified Explanation==

The abstract describes a secret decision tree test device that is used to evaluate a division condition at each node of a decision tree. This device performs secret calculations to learn the decision tree. It includes a memory and a processor. The processor is responsible for inputting a numerical attribute value vector, a label value vector, and a group information vector. These vectors contain specific numerical attribute values, label values, and grouping information of the data set used for learning the decision tree. The processor then calculates first to fourth frequencies using these vectors and evaluates the division condition using these frequencies.


==Original Abstract Submitted==

A secret decision tree test device configured to evaluate a division condition at each of a plurality of nodes of a decision tree when learning of the decision tree is performed by secret calculation, the secret decision tree test device includes a memory; and a processor configured to execute inputting a numerical attribute value vector composed of specific numerical attribute values of items of data included in a data set for learning of the decision tree, a label value vector composed of label values of the items of the data, and a group information vector indicating grouping of the items of the data into the nodes; and calculating, using the numerical attribute value vector, the label value vector, and the group information vector, first to fourth frequencies, to evaluate the division condition using the first to fourth frequencies.