公开(公告)号：US09697474B2

公开(公告)日：2017-07-04

申请号：US14096050

申请日：2013-12-04

Applicant: Google Inc.

Inventor： Yifang Liu ,  Konstantinos Katsiapis ,  Samuel Ieong ,  Roberto Bayardo

IPC: G06F17/00 ,  G06N5/04 ,  G06N99/00

CPC classification number: G06N99/005

Abstract: Multi-class classification by training a machine learning system based on training inputs each of which includes features and at least one class label. Each training input is assigned a membership value that can indicate if an entity having the features of the training input is a member of the class corresponding to the class label that is also included in the training input. To determine if an entity having test features is a member of several test classes, test inputs can be constructed where each input includes the test features and a class label corresponding to one of the test classes. The test inputs are processed by the trained machine learning system, which produces as outputs test membership values that represent the likelihood that the entity having the features in the test input belong to the test class corresponding to the test class label also included in the test input.

公开(公告)号：US20150154507A1

公开(公告)日：2015-06-04

申请号：US14096050

申请日：2013-12-04

Applicant: Google, Inc.

Inventor： Yifang Liu ,  Konstantinos Katsiapis ,  Samuel Ieong ,  Roberto Bayardo

IPC: G06N99/00

CPC classification number: G06N99/005

Abstract: Multi-class classification by training a machine learning system based on training inputs each of which includes features and at least one class label. Each training input is assigned a membership value that can indicate if an entity having the features of the training input is a member of the class corresponding to the class label that is also included in the training input. To determine if an entity having test features is a member of several test classes, test inputs can be constructed where each input includes the test features and a class label corresponding to one of the test classes. The test inputs are processed by the trained machine learning system, which produces as outputs test membership values that represent the likelihood that the entity having the features in the test input belong to the test class corresponding to the test class label also included in the test input.

Abstract translation: 通过训练基于训练输入的机器学习系统进行多类分类，每个训练输入包括特征和至少一个类标签。 每个训练输入被分配成员值，该值可以指示具有训练输入特征的实体是否也包括在训练输入中的类标签对应的类的成员。 为了确定具有测试特征的实体是否是几个测试类的成员，可以构建测试输入，其中每个输入包括测试特征和与其中一个测试类相对应的类标签。 测试输入由经过训练的机器学习系统处理，其产生作为输出测试成员资格值的输出，该成员值表示具有测试输入中的特征的实体属于与测试类标签相对应的测试类别的可能性，该测试类也包括在测试输入中 。