This repository is the official implementation of the paper “Jun-Xiang Mao, Wei Wang, Min-Ling Zhang. Label-Specific Multi-Semantics Metric Learning for Multi-Label Classification. In: Proceedings of the 32th International Joint Conference on Artificial Intelligence (IJCAI'23), Macao, China.”
Github link: https://github.com/Mao158/LIMIC
- MATLAB 2022b
- Statistics and Machine Learning Toolbox 12.4
- Bioinformatics Toolbox 4.16.1
- Parallel Computing Toolbox 7.7
To start, create a directory of your choice and copy the code there.
Set the path in your MATLAB to add the directory you just created.
This repository provides two demos on CAL500 and emotions multi-label data sets which shows the training and testing phase of the LIMIC. Other data sets is available from Mulan and PALM.
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LIMIC Demo This demo demonstrates how to implement LIMIC and how to make multi-label classification with LIMIC directly. You can run "LIMIC_Demo.m" to do it.
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MLKNN-LIMIC Demo LIMIC can be utilized to be coupled with similarity/distance-based multi-label classification algorithms. This demo demonstrates the implementation of MLKNN-LIMIC. You can run "MLKNN_LIMIC_Demo.m" to do it. Based on this, you can implement other coupling versions of LIMIC according to your requirements.