GHCF | Graph Heterogeneous Collaborative Filtering | Recommender System library

by chenchongthu Python Version: Current License: No License

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

kandi X-RAY | GHCF Summary

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

This is our implementation of the paper:.

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Quality

Security

License

Reuse

Support

GHCF has a low active ecosystem.

It has 20 star(s) with 3 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

GHCF has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of GHCF is current.

Quality

GHCF has no bugs reported.

Security

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

License

GHCF 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

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

GHCF 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.

Top functions reviewed by kandi - BETA

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

Create the network embeddings
Calculates the A - hat out of the dataset
Generates the A_hat tensor for each fold
Convert matrices to Tensor
Creates Laplace norm4
Convert matrices to tf Tensor
Create embedding matrix
R Get the adjacency matrix
Create adjacency matrix
Get sparsity split
Create a sparsity split
Calculate the N DCG at a given point
Create Laplace norm
Return the average of the values in a sequence
Load pretrained embeddings
Creates Laplace norm2
Creates Laplace norm1
Parse arguments
Creates Laplace norm3
Set early stopping strategy
Splits the A hat onto the node dropout
Create the GNC embedding
Create the GCN embedding
Create Gcmc embedding
Creates an embedding matrix
Sample test
Return a random sample of users

Get all kandi verified functions for this library.

GHCF Key Features

No Key Features are available at this moment for GHCF.

GHCF Examples and Code Snippets

No Code Snippets are available at this moment for GHCF.

Community Discussions

Trending Discussions on GHCF

Generate Powerset of length 4 using Java-8 is possible

QUESTION

Generate Powerset of length 4 using Java-8 is possible

Asked 2020-Jan-21 at 10:20

I have been able to generate the all permutation of length 4 from a string, the problem that I am facing now is that all the permutation have duplicates like {abcd) ,{adbc},{bcda}...which are all same as from Mathematical definition of set.

Is there a short version in java-8 where I can get the pure set?

My code that generated the all permutation:

...

ANSWER

Answered 2020-Jan-21 at 09:44

If you want to find the unique words (without considering order of characters, as you mentioned), you can do one additional step after permutation is done.

Source https://stackoverflow.com/questions/59837964

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

Vulnerabilities

No vulnerabilities reported

Install GHCF

You can download it from GitHub.
You can use GHCF 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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