int.feature.selection: Main function for integrative feature selection
In celehs/KESER: Knowledge Extraction via Sparse Embedding Regression (KESER)
View source: R/int-feature-selection.R
int.feature.selection R Documentation
Main function for integrative feature selection
Description
Main function for integrative feature selection
Usage
int.feature.selection(
X_full_lst,
Y_full_lst,
X_train_lst,
Y_train_lst,
X_valid_lst,
Y_valid_lst,
lambda_lst = NULL,
add.ridge = TRUE
)
Arguments
X_full_lst
...
Y_full_lst
...
X_train_lst
...
Y_train_lst
...
X_valid_lst
...
Y_valid_lst
...
lambda_lst
...
add.ridge
...
celehs/KESER documentation built on April 7, 2022, 9:35 a.m.
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.
View source: R/int-feature-selection.R
| int.feature.selection | R Documentation |
Main function for integrative feature selection
Description
Main function for integrative feature selection
Usage
int.feature.selection( X_full_lst, Y_full_lst, X_train_lst, Y_train_lst, X_valid_lst, Y_valid_lst, lambda_lst = NULL, add.ridge = TRUE )
Arguments
X_full_lst |
... |
Y_full_lst |
... |
X_train_lst |
... |
Y_train_lst |
... |
X_valid_lst |
... |
Y_valid_lst |
... |
lambda_lst |
... |
add.ridge |
... |
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.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.