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.

        classDiagram
  BaseEstimator <|-- LinearModel
  BaseEstimator <|-- SearchLight
  BaseEstimator <|-- _BaseDecoder
  BaseSpaceNet <|-- SpaceNetClassifier
  BaseSpaceNet <|-- SpaceNetRegressor
  CacheMixin <|-- BaseSpaceNet
  CacheMixin <|-- _BaseDecoder
  ClassifierMixin <|-- Decoder
  LinearModel <|-- LinearRegression
  LinearRegression <|-- BaseSpaceNet
  MultiOutputMixin <|-- DecoderRegressor
  MultiOutputMixin <|-- LinearRegression
  RegressorMixin <|-- DecoderRegressor
  RegressorMixin <|-- LinearRegression
  TransformerMixin <|-- SearchLight
  _BaseDecoder <|-- Decoder
  _BaseDecoder <|-- DecoderRegressor
  _BaseDecoder <|-- FREMClassifier
  _BaseDecoder <|-- FREMRegressor
  _HTMLDocumentationLinkMixin <|-- BaseEstimator
  _MetadataRequester <|-- BaseEstimator
  _SetOutputMixin <|-- TransformerMixin