Invention Grant
- Patent Title: Learning machine training based on plan types
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Application No.: US16512057Application Date: 2019-07-15
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Publication No.: US11861460B2Publication Date: 2024-01-02
- Inventor: Bharat Sri Vardhan Vemulapalli , Eric Etu , Marguerite Ellis
- Applicant: Hipmunk, Inc.
- Applicant Address: US CA San Francisco
- Assignee: Hipmunk, Inc.
- Current Assignee: Hipmunk, Inc.
- Current Assignee Address: US CA San Francisco
- Agency: SCHWEGMAN LUNDBERG & WOESSNER, P.A.
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G06F16/2457

Abstract:
A system for training a learning machine accesses a training database of reference metadata that describes reference plans that include reference first-type plans and reference second-type plans. Such plans may be travel plans or other plans. The system trains the learning machine to distinguish candidate first-type plans from candidate second-type plans. The training of the learning machine is based on a set of decision trees generated from randomly selected subsets of the reference metadata, and the randomly selected subsets each describe a corresponding randomly selected portion of the reference plans. The system then modifies the trained learning machine based on asymmetrical penalties for incorrectly distinguishing candidate first-type plans from candidate second-type plans. The system then provides the modified learning machine for run-time use in classifying plans.
Public/Granted literature
- US20210019649A1 LEARNING MACHINE TRAINING BASED ON PLAN TYPES Public/Granted day:2021-01-21
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