dynamic-time-warping | Dynamic Time Warping code in C/C++

by zkan C++ Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | dynamic-time-warping Summary

dynamic-time-warping is a C++ library. dynamic-time-warping has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

Dynamic Time Warping code in C/C++.

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Support

dynamic-time-warping has a low active ecosystem.

It has 20 star(s) with 10 fork(s). There are 4 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 0 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of dynamic-time-warping is current.

Quality

dynamic-time-warping has 0 bugs and 0 code smells.

Security

dynamic-time-warping has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

dynamic-time-warping code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

dynamic-time-warping does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

dynamic-time-warping releases are not available. You will need to build from source code and install.

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dynamic-time-warping Key Features

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dynamic-time-warping Examples and Code Snippets

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Community Discussions

Trending Discussions on dynamic-time-warping

How to use Dynamic Time warping with kNN in python

rpy2 Dynamic Time Warping (dtw) in python - windowing does not work

QUESTION

How to use Dynamic Time warping with kNN in python

Asked 2019-Nov-15 at 18:06

I have a time-series dataset with two lables (0 and 1). I am using Dynamic Time Warping (DTW) as a similarity measure for classification using k-nearest neighbour (kNN) as described in these two wonderful blog posts:

ANSWER

Answered 2019-Aug-20 at 07:25

You can use a custom metric for KNN. Therefore you only need to implement DTW yourself (or use/adapt any existing DTW implementation in python) [gist of this code].

Source https://stackoverflow.com/questions/57015499

QUESTION

rpy2 Dynamic Time Warping (dtw) in python - windowing does not work

Asked 2018-Jun-21 at 16:05

A now closed discussion shows how to use the R dtw package in python. This is a little clumsy, but the R dtw package is great and better than currently available python dtw implementations. Unfortunately, the windowing functions like the Sakoe-Chiba band do not work when trying to specify a "window.size". There appears to be an issue with the mapping to the argument. Note that "." in arguments is supposed to be replaced with "_" when using rpy2. But following this convention, the argument is not being used for some reason.

...

ANSWER

Answered 2018-Jun-21 at 16:05

Answering my own question in case anyone ever has the same issue. The problem is the argument mapping and the R three dots ellipsis ‘...’. This can be fixed by specifying the mapping manually.

Source https://stackoverflow.com/questions/50972285

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

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