Invention Grant
- Patent Title: Extracting interpretable features for classification of multivariate time series from physical systems
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Application No.: US14527413Application Date: 2014-10-29
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Publication No.: US09652716B2Publication Date: 2017-05-16
- Inventor: Abhishek Sharma , Haifeng Chen , Guofei Jiang , Om Prasad Patri
- Applicant: NEC Laboratories America, Inc.
- Applicant Address: JP Tokyo
- Assignee: NEC Corporation
- Current Assignee: NEC Corporation
- Current Assignee Address: JP Tokyo
- Agent Joseph Kolodka
- Main IPC: G06F15/00
- IPC: G06F15/00 ; G06F15/18 ; G06N5/04 ; G06N5/00

Abstract:
A method and system are provided. The method includes extracting shapelets from each of a plurality of time series dimensions of multi-dimensional time series data. The method further includes building a plurality of decision-tree classifiers, one for each time series dimension, responsive to the shapelets extracted therefrom. The method also includes generating a pairwise similarity matrix between respective different ones of the plurality of time series dimensions using the shapelets as intermediaries for determining similarity. The method additionally includes applying a feature selection technique to the matrix to determine respective feature weights for each of shapelet features of the shapelets and respective classifier weights for each of the decision-tree classifiers that uses the shapelet features. The method further includes combining decisions issued from the decision-tree classifiers to generate a final verdict of classification for a time series dimension responsive to the respective feature weights and the respective classifier weights.
Public/Granted literature
- US20150235139A1 EXTRACTING INTERPRETABLE FEATURES FOR CLASSIFICATION OF MULTIVARIATE TIME SERIES FROM PHYSICAL SYSTEMS Public/Granted day:2015-08-20
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