MultiModesPreferenceEstimation

You can run the code from main.py using the following command:

python main.py --model MMUP --corruption 0 --rank 100 --root 1.1 --iteration 10 --lambda 0.0001 --epoch 10 --mode-dimension 3 --key-dimension 5 --batch-size 256 --learning-rate 0.001

Name		Name	Last commit message	Last commit date
Latest commit History 94 Commits
cluster_bash		cluster_bash
config		config
datax		datax
evaluation		evaluation
experiment		experiment
figs		figs
layers		layers
logos		logos
models		models
plots		plots
prediction		prediction
providers		providers
tables		tables
templates		templates
utils		utils
.gitignore		.gitignore
Amazon Digital Music Tuning Results Analysis.ipynb		Amazon Digital Music Tuning Results Analysis.ipynb
Amazon Video Games Tuning Results Analysis.ipynb		Amazon Video Games Tuning Results Analysis.ipynb
LICENSE		LICENSE
ML1M Tuning Results Analysis.ipynb		ML1M Tuning Results Analysis.ipynb
Merge Datasets.ipynb		Merge Datasets.ipynb
Netflix Tuning Results Analysis.ipynb		Netflix Tuning Results Analysis.ipynb
README.md		README.md
Reproduce Amazon Digital Music Final Tables and Plots.ipynb		Reproduce Amazon Digital Music Final Tables and Plots.ipynb
Reproduce Amazon Video Games Final Tables and Plots.ipynb		Reproduce Amazon Video Games Final Tables and Plots.ipynb
Reproduce ML1M Final Tables and Plots.ipynb		Reproduce ML1M Final Tables and Plots.ipynb
Write Amazon Dataset to Disk in CSV.ipynb		Write Amazon Dataset to Disk in CSV.ipynb
environment.yml		environment.yml
generate_bash.py		generate_bash.py
generate_config.py		generate_config.py
getamazon.py		getamazon.py
getmovielens.py		getmovielens.py
getnetflix.py		getnetflix.py
gettaobao.py		gettaobao.py
getyahoo.py		getyahoo.py
interpretation_analysis.py		interpretation_analysis.py
main.py		main.py
preference_anaysis.csv		preference_anaysis.csv
reproduce_general_results.py		reproduce_general_results.py
tune_parameters.py		tune_parameters.py

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