Trains and tests prediction models
Usage
traintest(
y_train,
X_train,
y_test = NULL,
X_test = NULL,
family,
alpha,
method = c("glm.separate", "glm.glmtrans", "sparselink", "glm.common"),
alpha.init,
type,
trial = FALSE
)Arguments
- y_train
target of training samples: vector of length n
- X_train
features of training samples: \(n \times p\) matrix
- y_test
target of testing samples: vector of length \(m\)
- X_test
features of testing samples \(m \times p\) matrix
- family
character "gaussian" or "binomial"
- alpha
elastic net mixing parameter
- method
character vector
- alpha.init
elastic net mixing parameter for initial regressions
- type
character
- trial
see sparselink