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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.
Getting started
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Package details |
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| Author | Learned Pattern Similarity (LPS) for time series by Mustafa Gokce Baydogan |
| Maintainer | Mustafa Gokce Baydogan <baydoganmustafa@gmail.com> |
| License | GPL (>= 2) |
| Version | 1.0-5 |
| URL | http://www.mustafabaydogan.com/learned-pattern-similarity-lps.html |
| Package repository | View on CRAN |
| Installation |
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