公开(公告)号：US11593712B2

公开(公告)日：2023-02-28

申请号：US16865787

申请日：2020-05-04

Applicant: Google LLC

Inventor： Barron Webster ,  Irene Alvarado ,  Kyle Phillips ,  Alexander Chen ,  Jonas Pieter Halfdan Jongejan ,  Jordan Griffith ,  Amit Pitaru

IPC: G06N20/00 ,  G06F3/0485 ,  G06F16/28

Abstract: One or more processors may output for display, an interface including a data classification section including two or more class nodes, a training section including a training node, and an evaluation section including an evaluation node. At a first class node a first set of training data may be captured and at a second class node a second set of training data may be captured. In response to an input received at the training node, a classification model based on the first set of training data and the second set of training data may be trained. Evaluation data may be captured in an evaluation node, and using the trained classification model, classifications for each piece of the evaluation data may be determined. A visual representation of the classification for each piece of the evaluation data may be output for display within the evaluation node.

公开(公告)号：USD858570S1

公开(公告)日：2019-09-03

申请号：US29619904

申请日：2017-10-03

Applicant: Google LLC

Designer： Carlos Palacio ,  José Guizar Villalvazo ,  Jeffrey Schmidt ,  Elliot Burford ,  Barron Webster ,  Carsten Hinz

公开(公告)号：US20210342739A1

公开(公告)日：2021-11-04

申请号：US16865787

申请日：2020-05-04

Applicant: Google LLC

Inventor： Barron Webster ,  Irene Alvarado ,  Kyle Phillips ,  Alexander Chen ,  Jonas Pieter Halfdan Jongejan ,  Jordan Griffith ,  Amit Pitaru

IPC: G06N20/00 ,  G06F16/28 ,  G06F3/0485

Abstract: One or more processors may output for display, an interface including a data classification section including two or more class nodes, a training section including a training node, and an evaluation section including an evaluation node. At a first class node a first set of training data may be captured and at a second class node a second set of training data may be captured. In response to an input received at the training node, a classification model based on the first set of training data and the second set of training data may be trained. Evaluation data may be captured in an evaluation node, and using the trained classification model, classifications for each piece of the evaluation data may be determined. A visual representation of the classification for each piece of the evaluation data may be output for display within the evaluation node.