SGBT is also availabe on [CapyMOA] (https://capymoa.org/) python stream learning framework.
SGBT is now availabe on [MOA main branch] (https://github.com/Waikato/moa).
- datasets from Streaming Random Patches (SRP): https://github.com/hmgomes/StreamingRandomPatches/tree/master/datasets
- synthetic data sets:
LED_a_S="-s (ConceptDriftStream -s (generators.LEDGeneratorDrift -d 1) -d (ConceptDriftStream -s (generators.LEDGeneratorDrift -d 3) -d (ConceptDriftStream -s (generators.LEDGeneratorDrift -d 5) -d (generators.LEDGeneratorDrift -d 7) -w 50 -p 250000 ) -w 50 -p 250000 ) -w 50 -p 250000 -r $random_seed )"
LED_g_S="-s (ConceptDriftStream -s (generators.LEDGeneratorDrift -d 1) -d (ConceptDriftStream -s (generators.LEDGeneratorDrift -d 3) -d (ConceptDriftStream -s (generators.LEDGeneratorDrift -d 5) -d (generators.LEDGeneratorDrift -d 7) -w 50000 -p 250000 ) -w 50000 -p 250000 ) -w 50000 -p 250000 -r $random_seed )"
AGR_a_S="-s (ConceptDriftStream -s (generators.AgrawalGenerator -f 1) -d (ConceptDriftStream -s (generators.AgrawalGenerator -f 2) -d (ConceptDriftStream -s (generators.AgrawalGenerator ) -d (generators.AgrawalGenerator -f 4) -w 50 -p 250000 ) -w 50 -p 250000 ) -w 50 -p 250000 -r $random_seed )"
AGR_g_S="-s (ConceptDriftStream -s (generators.AgrawalGenerator -f 1) -d (ConceptDriftStream -s (generators.AgrawalGenerator -f 2) -d (ConceptDriftStream -s (generators.AgrawalGenerator ) -d (generators.AgrawalGenerator -f 4) -w 50000 -p 250000 ) -w 50000 -p 250000 ) -w 50000 -p 250000 -r $random_seed )"
RBF_m_S="-s (generators.RandomRBFGeneratorDrift -c 5 -s .0001 -r $random_seed -i $random_seed)"
RBF_f_S="-s (generators.RandomRBFGeneratorDrift -c 5 -s .001 -r $random_seed -i $random_seed)"
RBF_Bm_S="-s (generators.RandomRBFGeneratorDrift -c 2 -s .0001 -r $random_seed -i $random_seed)"
RBF_Bf_S="-s (generators.RandomRBFGeneratorDrift -c 2 -s .001 -r $random_seed -i $random_seed)"
RandomTreeGenerator_S="-s (generators.RandomTreeGenerator -r $random_seed -i $random_seed)"
RandomRBF5_S="-s (generators.RandomRBFGenerator -r $random_seed -i $random_seed -c 5)"
LED_S="-s (generators.LEDGenerator -i $random_seed)"
bash ./moa/src/main/scripts/reinit_conda.sh <conda_env_path> ./moa/src/main/scripts/conda.yml
bash ./moa/src/main/scripts/build_moa.sh <maven_repo_path> <conda_env_path>
bash moa/src/main/scripts/moa_gui_with_NN_support.sh <maven_repo_path> <conda_env_path> <djl_cache_dir>
bash <moa_source_root>/moa/src/main/scripts/run_moa.sh <dataset_dir> <results_dir> <djl_cache_dir> <maven_repo_path> <conda_env_path>
Notes:-
<moa_source_root>/moa/src/main/scripts/run_moa.sh
could be copied to any place and run.
Change dataset
variable in run_moa.sh
to change the data set.
Change learners
variable in run_moa.sh
to change learner command.