Invention Grant
- Patent Title: Ordinal time series classification with missing information
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Application No.: US17408852Application Date: 2021-08-23
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Publication No.: US12242542B2Publication Date: 2025-03-04
- Inventor: Cristian Lumezanu , Yuncong Chen , Takehiko Mizoguchi , Dongjin Song , Haifeng Chen , Jurijs Nazarovs
- Applicant: NEC Laboratories America, Inc.
- Applicant Address: US NJ Princeton
- Assignee: NEC Laboratories America, Inc.
- Current Assignee: NEC Laboratories America, Inc.
- Current Assignee Address: US NJ Princeton
- Agent Joseph Kolodka
- Main IPC: G06F16/906
- IPC: G06F16/906

Abstract:
A method classifies missing labels. The method computes, using a neural network model trained on training data, rank-based statistics of a feature of a time series segment to attempt to select two candidate labels from the training data that the segment most likely belongs to. The method classifies the segment using k-NN-based classification applied to the training data, responsive to the two candidate labels being present in the training data. The method classifies the segment by hypothesis testing, responsive to only one candidate label being present in the training data. The method classifies the segment into a class with higher values of the rank-based statistics from among a plurality of classes with different values of the rank-based statistics, responsive to no candidate labels being present in the training data. The method corrects a prediction by an applicable one of the classifying steps by majority voting with time windows.
Public/Granted literature
- US20220075822A1 ORDINAL TIME SERIES CLASSIFICATION WITH MISSING INFORMATION Public/Granted day:2022-03-10
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