Load Model (Scikit) with MOABB

This example shows how to use load the pretrained pipeline in MOABB.

# Authors: Igor Carrara <igor.carrara@inria.fr>
#
# License: BSD (3-clause)

from pickle import load

from moabb import set_log_level
from moabb.utils import setup_seed


set_log_level("info")

In this example, we will use the results computed by the following examples

• plot_benchmark

---

# Set up reproducibility of Tensorflow and PyTorch
setup_seed(42)

Loading the Scikit-learn pipelines

New model saves are namespaced by paradigm and benchmark suffix. Legacy model trees created by older MOABB versions are not moved and remain readable at their original paths.

with open(
    "../how_to_benchmark/results/Models_WithinSession/LeftRightImagery/benchmark/Zhou2016/1/0/csp+svm/fitted_model_best.pkl",
    "rb",
) as pickle_file:
    CSP_SVM_Trained = load(pickle_file)