ChatterNet | Code and Sample Data for ChatterNet : KDD

by LCS2-IIITD Python Version: Current License: LGPL-3.0

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

kandi X-RAY | ChatterNet Summary

ChatterNet is a Python library. ChatterNet has no bugs, it has no vulnerabilities, it has a Weak Copyleft License and it has low support. However ChatterNet build file is not available. You can download it from GitHub.

Code and Sample Data for ChatterNet: KDD 2020.

Support

Quality

Security

License

Reuse

Support

ChatterNet has a low active ecosystem.

It has 6 star(s) with 1 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

There are 0 open issues and 1 have been closed. On average issues are closed in 19 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of ChatterNet is current.

Quality

ChatterNet has 0 bugs and 0 code smells.

Security

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

ChatterNet code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

ChatterNet is licensed under the LGPL-3.0 License. This license is Weak Copyleft.

Weak Copyleft licenses have some restrictions, but you can use them in commercial projects.

Reuse

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

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

Installation instructions are not available. Examples and code snippets are available.

It has 3875 lines of code, 131 functions and 47 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

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

Train cross validation
Estimate the infected rate for each event
Estimate the parameters for a given event
Predict the best fit for a model
Estimate training parameters for training optimizer
Takes a list of Subreddit objects and processes them
Returns the number of temporal occurrences of a given sub_id
Compute the training error
Estimate infected rate distribution
Build model embedding
Network convolutional layer
Builds the model
Batch multiplication
Get information about the global graph
Get input features
Calculate rate tweets
Compute the score for each model
Generate a velocity vector of time t
Calculates the best fit error for the optimization
Estimate heterozygous rate distribution
Estimate the infected rate vector
Build an embedding model
R Predictive prediction function
R Predictive prediction
Build the model
Simulate ahawke time increment
Simulate time rescaling
Estimate the model parameters for an optimization

Get all kandi verified functions for this library.

ChatterNet Key Features

No Key Features are available at this moment for ChatterNet.

ChatterNet Examples and Code Snippets

No Code Snippets are available at this moment for ChatterNet.

Community Discussions

No Community Discussions are available at this moment for ChatterNet.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install ChatterNet

You can download it from GitHub.
You can use ChatterNet 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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