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advanced_examples

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external

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learning_curve

learning_curve

 
 

pipelines_DL

pipelines_DL

 
 

pipelines_braindecode

pipelines_braindecode

 
 

pipelines_codecarbon

pipelines_codecarbon

 
 

pipelines_grid

pipelines_grid

 
 

pipelines_save

pipelines_save

 
 

sample_pipelines

sample_pipelines

 
 

README.txt

README.txt

 
 

changing_download_directory.py

changing_download_directory.py

 
 

example_codecarbon.py

example_codecarbon.py

 
 

load_model.py

load_model.py

 
 

noplot_bids_conversion.py

noplot_bids_conversion.py

 
 

noplot_phmd_ml_spectrum.py

noplot_phmd_ml_spectrum.py

 
 

noplot_vr_pc_p300_different_epoch_size.py

noplot_vr_pc_p300_different_epoch_size.py

 
 

plot_Hinss2021_classification.py

plot_Hinss2021_classification.py

 
 

plot_benchmark.py

plot_benchmark.py

 
 

plot_benchmark_DL.py

plot_benchmark_DL.py

 
 

plot_benchmark_braindecode.py

plot_benchmark_braindecode.py

 
 

plot_benchmark_grid_search.py

plot_benchmark_grid_search.py

 
 

plot_braindecode.py

plot_braindecode.py

 
 

plot_cross_session_motor_imagery.py

plot_cross_session_motor_imagery.py

 
 

plot_cross_session_multiple_datasets.py

plot_cross_session_multiple_datasets.py

 
 

plot_cross_subject_ssvep.py

plot_cross_subject_ssvep.py

 
 

plot_disk_cache.py

plot_disk_cache.py

 
 

plot_explore_paradigm.py

plot_explore_paradigm.py

 
 

plot_fixed_interval_windows.py

plot_fixed_interval_windows.py

 
 

plot_within_session_p300.py

plot_within_session_p300.py

 
 

plot_within_session_ssvep.py

plot_within_session_ssvep.py

 
 

README.txt

Examples
-----------------

These examples demonstrate how to use MOABB, and its main concepts the
``dataset``, ``paradigm`` and ``evaluation``. Those examples are using
only a small number of subjects, and a small number of sessions, to
keep the execution time short. In practice, you should use all the
subjects and sessions available in the dataset.