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advanced_examples
advanced_examples
 
 
external
external
 
 
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.
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