nilearn.decoding: Decoding#

Decoding tools and algorithms.

Classes:

Decoder([estimator, mask, cv, param_grid, ...])

A wrapper for popular classification strategies in neuroimaging.

DecoderRegressor([estimator, mask, cv, ...])

A wrapper for popular regression strategies in neuroimaging.

FREMClassifier([estimator, mask, cv, ...])

State of the art decoding scheme applied to usual classifiers.

FREMRegressor([estimator, mask, cv, ...])

State of the art decoding scheme applied to usual regression estimators.

SpaceNetClassifier([penalty, loss, ...])

Classification learners with sparsity and spatial priors.

SpaceNetRegressor([penalty, l1_ratios, ...])

Regression learners with sparsity and spatial priors.

SearchLight(mask_img[, process_mask_img, ...])

Implement search_light analysis using an arbitrary type of classifier.