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Head-to-head comparisons with the relevance-chain, multifactor dimensionality reduction, and the pedigree disequilibrium test (PDT) methods were obtained.
In head-to-head comparisons with the relevance-chain, multifactor dimensionality reduction, and PDT methods, the results from visual interpretation of the KWII and TCI spectra performed satisfactorily.
Dawy et al. [ 9] proposed a relevance-chain method to identify the strongly associated lower-order interactions and build high-order interaction with the use of conditional mutual information.
13321_2016_121_MOESM4_ESM.py Additional file 4. The python script to compare binary relevance with chains of classifiers.
The performance of our approaches is compared with the performance of two algorithm adaptation methods (Multi-Label k-NN and Multi-Label C4.5) and five problem transformation methods (Binary Relevance, Classifier Chain, Calibrated Label Ranking with majority voting, the Quick Weighted method for pair-wise multi-label learning and the Label Powerset method).
(2) What is the relevance of supply chain transparency to supply chain sustainability governance?
In this section, we compare two methods that can handle missing annotations in the labels: binary relevance and classifiers chains.
Binary relevance and classifiers chain allow improving the predictivity of the models.
Different ways of addressing multi-label problems are explored and compared: label-powerset, binary relevance and classifiers chain.
Different ways of solving multi-label problems were explored and compared: label-powerset, binary relevance and classifiers chain.
In this work, we apply the three methods (label-powerset, binary relevance and classifiers chain) to a large BCRP/P-gp inhibition dataset derived from various sources.
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