Implementations of a number of functions used to mine numeric timeseries data. It covers the implementation of SAX transformation, univariate motif discovery (based on the random projection method), multivariate motif discovery (based on graph clustering), and several functions used for the ease of visualizing the motifs discovered. The details of SAX transformation can be found in J. Lin. E. Keogh, L. Wei, S. Lonardi, Experiencing SAX: A novel symbolic representation of time series, Data Mining and Knowledge Discovery 15 (2) (2007) 107144. Details on univariate motif discovery method implemented can be found in B. Chiu, E. Keogh, S. Lonardi, Probabilistic discovery of time series motifs, ACM SIGKDD, Washington, DC, USA, 2003, pp. 493498. Details on the multivariate motif discovery method implemented can be found in A. Vahdatpour, N. Amini, M. Sarrafzadeh, Towards unsupervised activity discovery using multidimensional motif detection in time series, IJCAI 2009 21st International Joint Conference on Artificial Intelligence.
Package details 


Author  Cheng Fan 
Date of publication  20150626 00:02:41 
Maintainer  Cheng Fan <[email protected]> 
License  GPL3 
Version  1.0 
Package repository  View on CRAN 
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