Zobrazeno 1 - 10
of 58
pro vyhledávání: '"Anthony J. Bagnall"'
Autor:
Aaron Bostrom, Anthony J. Bagnall, Michael Flynn, Jason Lines, James Large, Matthew Middlehurst
Publikováno v:
Machine Learning. 110:3211-3243
The Hierarchical Vote Collective of Transformation-based Ensembles (HIVE-COTE) is a heterogeneous meta ensemble for time series classification. HIVE-COTE forms its ensemble from classifiers of multiple domains, including phase-independent shapelets,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9270b64826150d77894f85105a9b6a74
https://doi.org/10.1007/s10994-021-06057-9
https://doi.org/10.1007/s10994-021-06057-9
Publikováno v:
Data Mining and Knowledge Discovery
Time Series Classification (TSC) involves building predictive models for a discrete target variable from ordered, real valued, attributes. Over recent years, a new set of TSC algorithms have been developed which have made significant improvement over
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::325375723dfae7b375e595a157209760
https://doi.org/10.1007/s10618-020-00727-3
https://doi.org/10.1007/s10618-020-00727-3
Publikováno v:
Data Mining and Knowledge Discovery. 34:1104-1135
At their core, many time series data mining algorithms reduce to reasoning about the shapes of time series subsequences. This requires an effective distance measure, and for last two decades most algorithms use Euclidean Distance or DTW as their core
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d7d439c61fed280361f84aa4ad72ff00
https://doi.org/10.1007/s10618-020-00695-8
https://doi.org/10.1007/s10618-020-00695-8
Autor:
Chotirat Ann Ratanamahatana, Yan Zhu, Chin-Chia Michael Yeh, Kaveh Kamgar, Hoang Anh Dau, Eamonn Keogh, Anthony J. Bagnall, Shaghayegh Gharghabi
Publikováno v:
IEEE/CAA Journal of Automatica Sinica. 6:1293-1305
The UCR time series archive–introduced in 2002, has become an important resource in the time series data mining community, with at least one thousand published papers making use of at least one data set from the archive. The original incarnation of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d0b358acb86474eae457737c1056b78b
https://doi.org/10.1109/jas.2019.1911747
https://doi.org/10.1109/jas.2019.1911747
Publikováno v:
Intelligent Data Analysis. 23:1073-1089
A family of algorithms for time series classification (TSC) involve running a sliding window across each series, discretising the window to form a word, forming a histogram of word counts over the dictionary, then constructing a classifier on the his
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::68c319639526a7e3b6bd16694fba0b95
https://doi.org/10.3233/ida-184333
https://doi.org/10.3233/ida-184333
Publikováno v:
Data Mining and Knowledge Discovery
Our hypothesis is that building ensembles of small sets of strong classifiers constructed with different learning algorithms is, on average, the best approach to classification for real world problems. We propose a simple mechanism for building small
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e201f95a3f0f061601efa337511d61a5
https://doi.org/10.1007/s10618-019-00638-y
https://doi.org/10.1007/s10618-019-00638-y
Publikováno v:
IEEE BigData
Time series classification (TSC) is home to a number of algorithm groups that utilise different kinds of discriminatory patterns. One of these groups describes classifiers that predict using phase dependant intervals. The time series forest (TSF) cla
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aa4e45e1a2302ee77091fc3471bd484a
https://ueaeprints.uea.ac.uk/id/eprint/79575/
https://ueaeprints.uea.ac.uk/id/eprint/79575/
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783030676575
Using bag of words representations of time series is a popular approach to time series classification. These algorithms involve approximating and discretising windows over a series to form words, then forming a count of words over a given dictionary.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7e739e29c894042e00712be86498515d
https://doi.org/10.1007/978-3-030-67658-2_38
https://doi.org/10.1007/978-3-030-67658-2_38
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030637989
SGAI Conf.
SGAI Conf.
Telemetry is an automatic system for monitoring environments in a remote or inaccessible area and transmitting data via various media. Data from telemetry stations can be used to produce early warning or decision supports in risky situations. However
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::482d87fb1372de988602f953e2c88c44
https://ueaeprints.uea.ac.uk/id/eprint/79173/
https://ueaeprints.uea.ac.uk/id/eprint/79173/
Publikováno v:
IJCNN
Nominal time series classification has been widely developed over the last years. However, to the best of our knowledge, ordinal classification of time series is an unexplored field, and this paper proposes a first approach in the context of the shap
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5ece880f93d8ef237a6891b00d3f2886
https://doi.org/10.1109/ijcnn48605.2020.9207200
https://doi.org/10.1109/ijcnn48605.2020.9207200