JMF

A general joint matrix factorization framework for data integration

JMF (Joint Matrix Factorization) is a MATLAB package to integrate multi-view data as well as prior relationship knowledge within or between multi-view data for pattern recognition and data mining.
Four update rules are adopted for solving JMF.
Two adapted prediction JMF models based on JMF are provided.

Check out our paper for a more complete description of the methods (L. Zhang and S. Zhang, IEEE Transactions on Fuzzy Systems, 2019).

Help

If you have any problems, comments or suggestions, please contact us at Lihua Zhang ([email protected]) or Shihua Zhang ([email protected]).

Name		Name	Last commit message	Last commit date
Latest commit History 6 Commits
JMF.m		JMF.m
JMF_prediction_L.m		JMF_prediction_L.m
JMF_prediction_R.m		JMF_prediction_R.m
JMF_synthetic_dataset1.m		JMF_synthetic_dataset1.m
JMF_synthetic_dataset2.m		JMF_synthetic_dataset2.m
JMF_synthetic_dataset3.m		JMF_synthetic_dataset3.m
JMF_synthetic_dataset4.m		JMF_synthetic_dataset4.m
MUR_updateH.m		MUR_updateH.m
MUR_updateW.m		MUR_updateW.m
Ne_updateH.m		Ne_updateH.m
Ne_updateW.m		Ne_updateW.m
PANLS_updateH.m		PANLS_updateH.m
PANLS_updateW.m		PANLS_updateW.m
PG_updateH.m		PG_updateH.m
PG_updateW.m		PG_updateW.m
README.md		README.md
README.txt		README.txt
StopCriterion_rule1.m		StopCriterion_rule1.m
StopCriterion_rule2.m		StopCriterion_rule2.m
compute_XHt_HHt.m		compute_XHt_HHt.m
compute_diff.m		compute_diff.m
compute_sumHRt.m		compute_sumHRt.m
compute_sumtheta_record.m		compute_sumtheta_record.m
get_gradH.m		get_gradH.m
get_gradW.m		get_gradW.m
main_demo.m		main_demo.m
normalize_WH_rowH.m		normalize_WH_rowH.m