cv.evaluate: Evaluate cv SPEAR object
In jgygi/SPEAR: SPEAR - Sparse Supervised Bayesian Factor Model for Multi-omic Analyses
cv.evaluate R Documentation
Evaluate cv SPEAR object
Description
Evaluate cv SPEAR object
Usage
cv.evaluate(
nlambda = 100,
calculate.factor.contributions = TRUE,
max_iter = 10000,
multinomial_loss = "deviance"
)
Arguments
nlambda
Number of lambdas (defaults to 100)
calculate.factor.contributions
Calculate factor contributions? When '$params$family == "multinomial"' or '"ordinal"' can save time to put 'FALSE'. Defaults to 'TRUE'.
max_iter
Maximum number of iterations (defaults to 10000)
multinomial_loss
Type of loss for when '$params$family == "multinomial"'. Can be '"deviance"' (default) or '"misclassification"'
jgygi/SPEAR documentation built on July 5, 2023, 5:35 p.m.
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| cv.evaluate | R Documentation |
Evaluate cv SPEAR object
Description
Evaluate cv SPEAR object
Usage
cv.evaluate(
nlambda = 100,
calculate.factor.contributions = TRUE,
max_iter = 10000,
multinomial_loss = "deviance"
)
Arguments
nlambda |
Number of lambdas (defaults to 100) |
calculate.factor.contributions |
Calculate factor contributions? When '$params$family == "multinomial"' or '"ordinal"' can save time to put 'FALSE'. Defaults to 'TRUE'. |
max_iter |
Maximum number of iterations (defaults to 10000) |
multinomial_loss |
Type of loss for when '$params$family == "multinomial"'. Can be '"deviance"' (default) or '"misclassification"' |
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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