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Dynamic Time Warping (DTW) library implementing lower bounds (LB_Keogh, LB_Improved...)

License: Apache License 2.0

Python 20.99% C++ 76.91% Makefile 2.11%
warping dtw lower-bounds c-plus-plus

lbimproved's Introduction

LBImproved C++ Library

Build Status

This library comes in the form of one short C++ header file. The documentation is in the C++ comments and in this file.

Key feature

  1. Fast Dynamic Time Warping nearest neighbor retrieval.

  2. Implementations of LB Koegh and LB Improved

  3. Companion to the following paper :

Daniel Lemire, Faster Retrieval with a Two-Pass Dynamic-Time-Warping Lower Bound, Pattern Recognition 42 (9), pages 2169-2180, 2009. http://arxiv.org/abs/0811.3301

Comments about this paper by Keogh's team:

 To our knowledge, there is only one paper that
 offers a plausible speedup based on a tighter 
 lower bound—Lemire (2009) suggests a mean speedup 
 of about 1.4 based on a tighter bound. 
 These results are reproducible, and testing on 
 more general data sets we obtained similar 
 results (...) (Wang et al. 2013)

BUILD

type "make"

make
./unittesting
./benchmark
./example

Simple code example

See example.cpp.

Other libraries

  • dtwclust is an R Package for Time Series Clustering Along with Optimizations for DTW

lbimproved's People

Contributors

herrmannm avatar lemire avatar

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lbimproved's Issues

Unable to compile on VS2008 (vista)

I want to run it on visual studio 2008 (Vista). Can you please tell me the
steps involved to compile and execute the program successfully.

Original issue reported on code.google.com by [email protected] on 23 Mar 2009 at 11:05

Examples on source and data

Could you post a simple example on how to use this as library? Moreover, a sample on how the data and class labels should look like. It would help others immensely.

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