Invention Grant
- Patent Title: Methods and systems for automatic selection of classification and regression trees
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Application No.: US11649399Application Date: 2007-01-04
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Publication No.: US09330127B2Publication Date: 2016-05-03
- Inventor: Dan Steinberg , Nicholas Scott Cardell
- Applicant: Dan Steinberg , Nicholas Scott Cardell
- Applicant Address: US CA San Diego
- Assignee: HEALTH CARE PRODUCTIVITY, INC.
- Current Assignee: HEALTH CARE PRODUCTIVITY, INC.
- Current Assignee Address: US CA San Diego
- Agency: Innatricity, LLC
- Agent Herbert L. Lacey, III
- Main IPC: G06F17/30
- IPC: G06F17/30 ; G06K9/62 ; G06N99/00

Abstract:
The present invention provides a method and system for automatically identifying and selecting preferred classification and regression trees. The invention is used to identify a specific decision tree or group of trees that are consistent across train and test samples in node-specific details that are often important to decision makers. Specifically, for a tree to be identified as preferred by this system, the train and test samples must both agree on key measures for every terminal node of the tree. In addition to this node-by-node criterion, an additional tree selection method may be imposed. Accordingly, the train and test samples rank order the nodes on a relevant measure in the same way. Both consistency criteria may be applied in a fuzzy manner in which agreement must be close but need not be exact.
Public/Granted literature
- US20080168011A1 Methods and systems for automatic selection of classification and regression trees Public/Granted day:2008-07-10
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