Basic baseline models with scikit-learn LinearRegression or RidgeCV

trained_encoding_models_basic/README.rtf

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+\f0\fs24 \cf0 Models trained with default parameters and features from the tutorial:\
+Trained around Jan 26, 2025.\
+\
+modality = "all"  #@param ["visual", "audio", "language", "all"]\
+\
+excluded_samples_start = 5  #@param \{type:"slider", min:0, max:20, step:1\}\
+\
+excluded_samples_end = 5  #@param \{type:"slider", min:0, max:20, step:1\}\
+\
+hrf_delay = 3  #@param \{type:"slider", min:0, max:10, step:1\}\
+\
+stimulus_window = 5  #@param \{type:"slider", min:1, max:20, step:1\} # how much history to use\
+\
+movies_train = ["friends-s01", "friends-s02", "friends-s03", "friends-s04", "friends-s05", "movie10-bourne", "movie10-figures", "movie10-life", "movie10-wolf"] # @param \{allow-input: true\}\
+\
+movies_val = ["friends-s06"] # @param \{allow-input: true\}\
+\
+One}

trained_encoding_models_basic/trained_encoding_model_sub-01_modality-all_sklearn_LinearRegression.npy

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trained_encoding_models_basic/trained_encoding_model_sub-01_modality-all_sklearn_RidgeCV.npy

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trained_encoding_models_basic/trained_encoding_model_sub-02_modality-all_sklearn_LinearRegression.npy

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trained_encoding_models_basic/trained_encoding_model_sub-02_modality-all_sklearn_RidgeCV.npy

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trained_encoding_models_basic/trained_encoding_model_sub-03_modality-all_sklearn_LinearRegression.npy

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trained_encoding_models_basic/trained_encoding_model_sub-05_modality-all_sklearn_LinearRegression.npy

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trained_encoding_models_basic/trained_encoding_model_sub-05_modality-all_sklearn_RidgeCV.npy

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