nilearn.decoding: Decoding¶
Decoding tools and algorithms.
Classes¶
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A wrapper for popular classification strategies in neuroimaging.  | 
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A wrapper for popular regression strategies in neuroimaging.  | 
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State of the art decoding scheme applied to usual classifiers.  | 
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State of the art decoding scheme applied to usual regression estimators.  | 
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Classification learners with sparsity and spatial priors.  | 
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Regression learners with sparsity and spatial priors.  | 
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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
  LinearModel <|-- LinearRegression
  LinearRegression <|-- BaseSpaceNet
  MultiOutputMixin <|-- DecoderRegressor
  MultiOutputMixin <|-- FREMRegressor
  MultiOutputMixin <|-- LinearRegression
  RegressorMixin <|-- LinearRegression
  TransformerMixin <|-- SearchLight
  _BaseDecoder <|-- Decoder
  _BaseDecoder <|-- DecoderRegressor
  _BaseDecoder <|-- FREMClassifier
  _BaseDecoder <|-- FREMRegressor
  _ClassifierMixin <|-- Decoder
  _ClassifierMixin <|-- FREMClassifier
  _ClassifierMixin <|-- SpaceNetClassifier
  _HTMLDocumentationLinkMixin <|-- BaseEstimator
  _MetadataRequester <|-- BaseEstimator
  _RegressorMixin <|-- DecoderRegressor
  _RegressorMixin <|-- FREMRegressor
  _RegressorMixin <|-- SpaceNetRegressor
  _SetOutputMixin <|-- TransformerMixin