Invention Publication
- Patent Title: MACHINE LEARNING RISK DETERMINATION SYSTEM FOR TREE BASED MODELS
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Application No.: US18471659Application Date: 2023-09-21
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Publication No.: US20240273390A1Publication Date: 2024-08-15
- Inventor: Brian Duke , David Zaleta
- Applicant: Experian Information Solutions, Inc.
- Applicant Address: US CA Costa Mesa
- Assignee: Experian Information Solutions, Inc.
- Current Assignee: Experian Information Solutions, Inc.
- Current Assignee Address: US CA Costa Mesa
- Main IPC: G06N5/045
- IPC: G06N5/045 ; G06F16/901 ; G06N7/01 ; G06N20/00

Abstract:
The present disclosure describes systems and methods for determining correlation codes for tree-based decisioning models. In one embodiment, a method for determining correlation codes in a tree-based decision model includes: assigning each decision node in a tree-based decision model to a correlation code; initializing a risk sum for each correlation code; calculating, for all decision nodes in the tree-based decision model, a difference in risk between child nodes and respective parent nodes; updating the risk sum for each correlation code associated with the decision node used in the decision for the node; determining the feature with the highest risk sum; and determining the correlation code associated with the determined decision node.
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