LPStimeSeries: Learned Pattern Similarity and Representation for Time Series

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.

AuthorLearned Pattern Similarity (LPS) for time series by Mustafa Gokce Baydogan
Date of publication2015-03-27 18:54:54
MaintainerMustafa Gokce Baydogan <baydoganmustafa@gmail.com>
LicenseGPL (>= 2)

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