This code mainly spent more than a label K-nearest neighbor method (MLKNN) to achieve the multi-label data classification

mLknnMATLAB\data\test_100.mat
...........\....\test_data.mat
...........\....\train_300.mat
...........\....\train_400.mat
...........\main.m
...........\MetricFunction\Average_precision.m
...........\..............\coverage.m
...........\..............\Hamming_loss.m
...........\..............\One_error.m
...........\..............\Ranking_loss.m
...........\test.m
...........\train.m
...........\data
...........\MetricFunction
mLknnMATLAB

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