FastEE: Fast Ensembles of Elastic Distances This is the source code for FastEE - Faster version of the Ensembles of Elastic Distances (EE). In particular, FastEE tackles the long training time of EE. This code only focus on training EE.
Running from terminal
- Training the individual classifers
- java -Xmx14g -Xms14g -cp $LIBDIR: experiments.IndividualClassifierEE $OUTPUTDIR $DATASETDIR $PROBLEM $DISTANCE
- java -Xmx14g -Xms14g -cp $LIBDIR: experiments.IndividualClassifierLbEE $OUTPUTDIR $DATASETDIR $PROBLEM $DISTANCE
- java -Xmx14g -Xms14g -cp $LIBDIR: experiments.IndividualClassifierFastEE $OUTPUTDIR $DATASETDIR $PROBLEM $DISTANCE
- java -Xmx14g -Xms14g -cp $LIBDIR: experiments.IndividualClassifierApproxEE $OUTPUTDIR $DATASETDIR $PROBLEM $DISTANCE $NSAMPLES $NRUNS
- Training the whole ensemble
- java -Xmx14g -Xms14g -cp $LIBDIR: experiments.TrainElasticEnsembles $OUTPUTDIR $DATASETDIR $PROBLEM $CLASSIFIER $NSAMPLES
Running from Bash Script
- bash TrainIndividualClasssifiers.sh [-p <Dataset_Name>] [-c <EE|LbEE|FastEE|ApproxEE>] [-d <Dataset_Directory>] [-o <Output_Directory>] [-s <Number_of_Samples>] [-r <Number_of_Runs>]
- bash TrainEnsembles.sh [-p <Dataset_Name>] [-c <EE|LbEE|FastEE|ApproxEE>] [-d <Dataset_Directory>] [-o <Output_Directory>] [-s <Number_of_Samples>]