ExplicitLossMinimization

Explicit Loss Minimization

QuaPy makes available several Explicit Loss Minimization (ELM) methods, including SVM(Q), SVM(KLD), SVM(NKLD), SVM(AE), or SVM(RAE). These methods require to first download the svmperf package, apply the patch svm-perf-quantification-ext.patch, and compile the sources. The script prepare_svmperf.sh does all the job. Simply run:

./prepare_svmperf.sh

The resulting directory svm_perf_quantification contains the patched version of svmperf with quantification-oriented losses.

The svm-perf-quantification-ext.patch is an extension of the patch made available by Esuli et al. 2015 that allows SVMperf to optimize for the Q measure as proposed by Barranquero et al. 2015 and for the KLD and NKLD measures as proposed by Esuli et al. 2015. This patch extends the above one by also allowing SVMperf to optimize for AE and RAE. See Methods.md for more details and code examples.