L1_CCA_CV: L1-penalized SCCA with CV
In agisga/FDRcorrectedSCCA: FDR-Corrected Sparse Canonical Correlation Analysis
Description
L1-penalized SCCA with hyperparameter choice via k-fold cross-validation
Usage
1
L1_CCA_CV(X, Y, lambda_X, lambda_Y, n_folds = 5)
Details
The considered search space is effectively one-dimensional by considering
penalty pairs (lambda_X[1], lambda_Y[1]), (lambda_X[2], lambda_Y[2]), etc.
The number of cross-validation folds can be specified.
agisga/FDRcorrectedSCCA documentation built on May 20, 2019, 6:45 p.m.
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Description
L1-penalized SCCA with hyperparameter choice via k-fold cross-validation
Usage
1 | L1_CCA_CV(X, Y, lambda_X, lambda_Y, n_folds = 5)
|
Details
The considered search space is effectively one-dimensional by considering penalty pairs (lambda_X[1], lambda_Y[1]), (lambda_X[2], lambda_Y[2]), etc. The number of cross-validation folds can be specified.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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