Bitbucket.org / len_feremans / lcif_knn_pub

Public implementation of "Combining Instance and Feature neighbors for Efficient Multi-label Classification" published in 2017 IEEE International Conference on Data Science and Advanced Analytics (DSAA). Multi-label classification problems occur naturally in different domains like text categorisation or scene classification . In this algorithm we use a combination of two variations of k nearest neighborhoods (kNN) where the first neighborhood is computed instance (or row) based and the second neighborhood is feature (or column) based. Our implementation scales to sparse datasets with millions of rows, features and labels. Experimental scripts are also provided for reproducing results presented in the paper.

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