IPM3F
Source code and data for the paper "Nonparametric Max-Margin Matrix Factorization for Collaborative Prediction" accepted to NIPS'2012 and "Fast Max-Margin Matrix Factorization with Data Augmentation" accepted to ICML'2013
Install / Use
npx skills add chokkyvista/iPM3FInstalls into whichever agent you are using.
README
To run iPM3F (M3F and iBPM3F likewise):
-
set working dir in MATLAB to iPM3F
-
load data
load('../data/MovieLens-1M.mat');
- a little bit configuration [OPTIONAL]
% defaults to 'weak' & 'no validation' weakopts = []; % for the 'weak' setting validid = 1; % use the 1st validation set
- compile mex-files and initialize
init;
- set range for regularization constant tuning [OPTIONAL]
% defaults to the entire range rid_s = 1; rid_t = numel(regvals); % tune all the candidate values
- turn on parallel computing and logging [OPTIONAL]
matlabpool open <your_profile>; diary(fullfile(savedir, 'log.txt'));
- train the model and test performance
train_ipm3f;
- turn off parallel computing and logging [OPTIONAL]
diary off; matlabpool close;
Put together:
cd iPM3F; load('../data/MovieLens-1M.mat'); init; train_ipm3f;
To run GiPM3F or GM3F, you may need to download daSVM (https://github.com/chokkyvista/daSVM) as well and put it at the same level as the iPM3F root directory:
- daSVM
- iPM3F |- GM3F |- GiPM3F |- IBP |- common |- data
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