Skip to content

xcgydfjjjderg/v2.0

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

5 Commits
 
 
 
 

Repository files navigation

Installation

python setup.py install

Requirements

  • Python 3.7
  • TensorFlow (2.0)
  • pandas

Usage

To reproduce the experiments mentioned in the paper you can run the following commands:

Douban

python train.py -d douban --accum stack -do 0.7 -nleft -nb 2 -e 200 --features --feat_hidden 64 --testing 

Flixster

python train.py -d flixster --accum stack -do 0.7 -nleft -nb 2 -e 200 --features --feat_hidden 64 --testing

Yahoo Music

python train.py -d yahoo_music --accum stack -do 0.7 -nleft -nb 2 -e 200 --features --feat_hidden 64 --testing

##Description

graph autoencoders on Ml-100k folder based on ML-100k dataset,you run the train.py file directly.graph autoencoder on three datesets folder based on Douban,Flixster,and Yahoo Music datasets,you run above mentioned commands.All datasets are already in the corresponding folder.

About

Graph autoencoder correlation algorithm

Resources

Stars

Watchers

Forks

Packages

No packages published