公开(公告)号：US11775504B2

公开(公告)日：2023-10-03

申请号：US17855693

申请日：2022-06-30

Applicant: Intuit Inc.

Inventor： Vitor R. Carvalho ,  Janani Kalyanam ,  Leah Zhao ,  Peter Ouyang

IPC: G06F16/23 ,  G06F16/2458 ,  G06F16/22

CPC classification number: G06F16/2365 ,  G06F16/2246 ,  G06F16/2462

Abstract: A method for computer estimations based on statistical tree structures involves obtaining a statistical tree structure for reference elements. The statistical tree structure includes leaf nodes segmenting a statistic for a data label according to data features in the reference elements, and intermediate nodes connecting a first node to the leaf nodes. Each of the first node and the intermediate nodes provide a branching based on one of the data features. The method further includes obtaining target data, including values for the data features, and a value for the data label. The method also includes selecting the first node, associated with a first data feature, traversing the statistical tree structure to a leaf node by matching the values of the data features to the branching of the intermediate nodes, and assessing the value for the data label in the target data based on the statistic associated with the leaf node.

公开(公告)号：US20220335035A1

公开(公告)日：2022-10-20

申请号：US17855693

申请日：2022-06-30

Applicant: Intuit Inc.

Inventor： Vitor R. Carvalho ,  Janani Kalyanam ,  Leah Zhao ,  Peter Ouyang

IPC: G06F16/23 ,  G06F16/2458 ,  G06F16/22

Abstract: A method for computer estimations based on statistical tree structures involves obtaining a statistical tree structure for reference elements. The statistical tree structure includes leaf nodes segmenting a statistic for a data label according to data features in the reference elements, and intermediate nodes connecting a first node to the leaf nodes. Each of the first node and the intermediate nodes provide a branching based on one of the data features. The method further includes obtaining target data, including values for the data features, and a value for the data label. The method also includes selecting the first node, associated with a first data feature, traversing the statistical tree structure to a leaf node by matching the values of the data features to the branching of the intermediate nodes, and assessing the value for the data label in the target data based on the statistic associated with the leaf node.

公开(公告)号：US11409732B2

公开(公告)日：2022-08-09

申请号：US16745604

申请日：2020-01-17

Applicant: Intuit Inc.

Inventor： Vitor R. Carvalho ,  Janani Kalyanam ,  Leah Zhao ,  Peter Ouyang

IPC: G06F16/23 ,  G06F16/2458 ,  G06F16/22

Abstract: A method for computer estimations based on statistical tree structures involves obtaining a statistical tree structure for reference elements. The statistical tree structure includes leaf nodes segmenting a statistic for a data label according to data features in the reference elements, and intermediate nodes connecting a first node to the leaf nodes. Each of the first node and the intermediate nodes provide a branching based on one of the data features. The method further includes obtaining target data, including values for the data features, and a value for the data label. The method also includes selecting the first node, associated with a first data feature, traversing the statistical tree structure to a leaf node by matching the values of the data features to the branching of the intermediate nodes, and assessing the value for the data label in the target data based on the statistic associated with the leaf node.

公开(公告)号：US20210224247A1

公开(公告)日：2021-07-22

申请号：US16745604

申请日：2020-01-17

Applicant: Intuit Inc.

Inventor： Vitor R. Carvalho ,  Janani Kalyanam ,  Leah Zhao ,  Peter Ouyang

IPC: G06F16/23 ,  G06F16/22 ,  G06F16/2458

Abstract: A method for computer estimations based on statistical tree structures involves obtaining a statistical tree structure for reference elements. The statistical tree structure includes leaf nodes segmenting a statistic for a data label according to data features in the reference elements, and intermediate nodes connecting a first node to the leaf nodes. Each of the first node and the intermediate nodes provide a branching based on one of the data features. The method further includes obtaining target data, including values for the data features, and a value for the data label. The method also includes selecting the first node, associated with a first data feature, traversing the statistical tree structure to a leaf node by matching the values of the data features to the branching of the intermediate nodes, and assessing the value for the data label in the target data based on the statistic associated with the leaf node.