A Worst Case Analysis of Calibrated Label Ranking Multi-label Classification Method

Most multi-label classification methods are evaluated on real datasets, which is a good practice for comparing the performance among methods on the average scenario. Due to the large amount of factors to consider, this empirical approach does not explain, nor does show the factors impacting the performance. A reasonable way to understand some of the performance’s factors of multi-label methods independently of the context is to find a mathematical proof about them. In this paper, mathematical proofs are given for …

analysis case classification ranking