Data Augmentation with Suboptimal Warping for Time-Series Classification
نویسندگان
چکیده
منابع مشابه
Multivariate time series classification with parametric derivative dynamic time warping
Multivariate time series (MTS) data are widely used in a very broad range of fields, including medicine, finance, multimedia and engineering. In this paper a new approach for MTS classification, using a parametric derivative dynamic time warping distance, is proposed. Our approach combines two distances: the DTW distance between MTS and the DTW distance between derivatives of MTS. The new dista...
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Dynamic time warping (DTW), which finds the minimum path by providing non-linear alignments between two time series, has been widely used as a distance measure for time series classification and clustering. However, DTW does not account for the relative importance regarding the phase difference between a reference point and a testing point. Thismay lead tomisclassification especially in applica...
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Dynamic Time Warping (DTW) has been widely used in time series domain as a distance function for similarity search. Several works have utilized DTW to improve the classification accuracy as it can deal with local time shiftings in time series data by non-linear warping. However, some types of time series data do have several segments that one segment should not be compared to others even though...
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We propose an approach to embed time series data in a vector space based on the distances obtained from Dynamic Time Warping (DTW), and to classify them in the embedded space. Under the problem setting in which both labeled data and unlabeled data are given beforehand, we consider three embeddings, embedding in a Euclidean space by MDS, embedding in a Pseudo-Euclidean space, and embedding in a ...
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Dynamic Time Warping (DTW) distance has been effectively used in mining time series data in a multitude of domains. However, DTW, in its original formulation, is extremely inefficient in comparing long sparse time series, which mostly contain zeros and unevenly spaced non-zero observations. Original DTW distance does not take advantage of the sparsity, and thus, incur a prohibitively large comp...
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ژورنال
عنوان ژورنال: Sensors
سال: 2019
ISSN: 1424-8220
DOI: 10.3390/s20010098