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Multivariate Pattern Analysis in Python |
Inheritance diagram for mvpa.clfs.glmnet:
GLM-Net (GLMNET) regression classifier.
Bases: mvpa.measures.base.Sensitivity
SensitivityAnalyzer that reports the weights GLMNET trained on a given Dataset.
Note
Available state variables:
(States enabled by default are listed with +)
Initialize the analyzer with the classifier it shall use.
Parameters: |
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Bases: mvpa.clfs.glmnet._GLMNET
GLM-NET Multinomial Classifier.
This is the GLM-NET algorithm from
Friedman, J., Hastie, T. and Tibshirani, R. (2008) Regularization Paths for Generalized Linear Models via Coordinate Descent. http://www-stat.stanford.edu/~hastie/Papers/glmnet.pdf
parameterized to be a multinomial classifier.
See GLMNET_Class for the gaussian regression version.
Note
Available state variables:
(States enabled by default are listed with +)
See also
Please refer to the documentation of the base class for more information:
_GLMNET
Initialize GLM-Net multinomial classifier.
See the help in R for further details on the parameters
Parameters: |
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Bases: mvpa.clfs.glmnet._GLMNET
GLM-NET Gaussian Regression Classifier.
This is the GLM-NET algorithm from
Friedman, J., Hastie, T. and Tibshirani, R. (2008) Regularization Paths for Generalized Linear Models via Coordinate Descent. http://www-stat.stanford.edu/~hastie/Papers/glmnet.pdf
parameterized to be a regression.
See GLMNET_C for the multinomial classifier version.
Note
Available state variables:
(States enabled by default are listed with +)
See also
Please refer to the documentation of the base class for more information:
_GLMNET
Initialize GLM-Net.
See the help in R for further details on the parameters
Parameters: |
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