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