Invention Grant
- Patent Title: Automatic feature learning from a relational database for predictive modelling
-
Application No.: US15714140Application Date: 2017-09-25
-
Publication No.: US10762111B2Publication Date: 2020-09-01
- Inventor: Beat Buesser , Thanh Lam Hoang , Mathieu Sinn , Ngoc Minh Tran
- Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Applicant Address: US NY Armonk
- Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee Address: US NY Armonk
- Agency: Griffiths & Seaton PLLC
- Main IPC: G06F17/00
- IPC: G06F17/00 ; G06F16/28 ; G06N3/08 ; G06F16/2455 ; G06N5/02 ; G06N3/04 ; G06N20/00 ; G06N7/00 ; G06N5/00

Abstract:
Embodiments for automatic feature learning for predictive modelling in a computing environment by a processor. A first table and a second table are joined based on an edge between the first table and the second table defined by an entity graph thereby creating a resulting joined table that is connected by a column of data. The resulting joined table is used as an input into one or more neural network operations that transform the resulting joined table to one or more features to predict a target variable.
Public/Granted literature
- US20190095515A1 AUTOMATIC FEATURE LEARNING FROM A RELATIONAL DATABASE FOR PREDICTIVE MODELLING Public/Granted day:2019-03-28
Information query