Description Usage Arguments Value
View source: R/package_functions.R
Train a multi-response elastic-net regression for prediction using cross-validation to select lambda
1 2 | predictExpression(training_x, training_y, prediction_x,
lambda_mse = TRUE, family = "mgaussian", ...)
|
training_x |
A cell by gene expression matrix of training predictor data |
training_y |
A cell by gene expression matrix of training outcome data |
prediction_x |
A cell by gene expression matrix of testing predictor data |
lambda_mse |
Whether to select the lambda that minimizes the cross-validation, default TRUE |
family |
family parameter passed on to the glmnet function, default 'mgaussian' |
... |
additional parameters to pass on to the glmnet function |
Returns a list of the predicted outcome and model fit glmnet object
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