DTCR | Learning Representations for Time Series Clustering | Machine Learning library

by qianlima-lab Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | DTCR Summary

DTCR is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning applications. DTCR has no bugs, it has no vulnerabilities and it has low support. However DTCR build file is not available. You can download it from GitHub.

The paper "Learning Representations for Time Series Clustering" accepted by 2019 Neural Information Processing Systems (NeurIPS). Jiawei Zheng and Sen Li equally contributed to this work.

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Quality

Security

License

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Support

DTCR has a low active ecosystem.

It has 63 star(s) with 20 fork(s). There are 8 watchers for this library.

It had no major release in the last 6 months.

There are 8 open issues and 0 have been closed. On average issues are closed in 132 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of DTCR is current.

Quality

DTCR has 0 bugs and 0 code smells.

Security

DTCR has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

DTCR code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

DTCR 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

DTCR releases are not available. You will need to build from source code and install.

DTCR has no build file. You will be need to create the build yourself to build the component from source.

Top functions reviewed by kandi - BETA

kandi has reviewed DTCR and discovered the below as its top functions. This is intended to give you an instant insight into DTCR implemented functionality, and help decide if they suit your requirements.

Evaluate the clustering for a label
Performs the clustering
Calculate a random index based on the clustering

Get all kandi verified functions for this library.

DTCR Key Features

No Key Features are available at this moment for DTCR.

DTCR Examples and Code Snippets

No Code Snippets are available at this moment for DTCR.

Community Discussions

Trending Discussions on DTCR

Lambda-Local not recognized as internal or external command

QUESTION

Lambda-Local not recognized as internal or external command

Asked 2019-Jul-26 at 08:46

Hi I am working on a lambda function on aws environment(node.js). Whereby to test the function locally, I was using lambda-local utility. Now might be due to version changes, it's throwing error

lambda-local' is not recognized as an internal or external command, operable program or batch file.

But I can't figure out how to make it work. I tried downgrading to a previous version of lambda-local to no avail. Also there's nothing much over the internet which deals with some kind of issue.

versions: npm version : 6.9.0 node version: v10.16.0 lambda-local: (I have tried: 1.6.3,1.5.2,1.5.0)

current package-lock.json depenedency of lambda-local

...

ANSWER

Answered 2019-Jul-26 at 08:46

lambda-local is not in your path which is why you are getting that error.

By default if you run the following on windows

Source https://stackoverflow.com/questions/57215468

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

Vulnerabilities

No vulnerabilities reported

Install DTCR

You can download it from GitHub.
You can use DTCR like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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