Fast classification of univariate and multivariate time series through shapelet discovery

Josif Grabocka; Martin Wistuba; Lars Schmidt-Thieme

doi:10.1007/s10115-015-0905-9

ScienceGate Book Chapters

JOURNAL ARTICLE

Fast classification of univariate and multivariate time series through shapelet discovery

Josif Grabocka Martin Wistuba Lars Schmidt-Thieme

Year: 2015 Journal: Knowledge and Information Systems Vol: 49 (2)Pages: 429-454 Publisher: Springer Science+Business Media

DOI: 10.1007/s10115-015-0905-9

Get Full-Text PDF Get Analytical Report

Keywords:

Univariate Multivariate statistics Computer science Data mining Pruning Cluster analysis Pattern recognition (psychology) Scale (ratio) Range (aeronautics) Artificial intelligence Set (abstract data type) Euclidean distance Machine learning

Metrics

Cited By

2.72

FWCI (Field Weighted Citation Impact)

Refs

0.92

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Time Series Analysis and Forecasting

Physical Sciences → Computer Science → Signal Processing

Complex Systems and Time Series Analysis

Social Sciences → Economics, Econometrics and Finance → Economics and Econometrics

Music and Audio Processing

Physical Sciences → Computer Science → Signal Processing

Fast classification of univariate and multivariate time series through shapelet discovery

Metrics

Citation History

Topics

Related Documents

Efficient Shapelet Discovery for Time Series Classification

Shapelet Discovery by Lazy Time Series Classification

ShapeFormer: Shapelet Transformer for Multivariate Time Series Classification

A scalable shapelet discovery for time series classification

Method of shapelet discovery for time series ordinal classification