Learned Pattern Similarity (LPS) for time series. Implements a novel approach to model the dependency structure in time series that generalizes the concept of autoregression to local auto-patterns. Generates a pattern-based representation of time series along with a similarity measure called Learned Pattern Similarity (LPS). Introduces a generalized autoregressive kernel.This package is based on the 'randomForest' package by Andy Liaw.
|Author||Learned Pattern Similarity (LPS) for time series by Mustafa Gokce Baydogan|
|Date of publication||2015-03-27 18:54:54|
|Maintainer||Mustafa Gokce Baydogan <firstname.lastname@example.org>|
|License||GPL (>= 2)|
|Package repository||View on CRAN|
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