View source: R/FeatureSelection.R
lasso.cv.select.feature | R Documentation |
Perform multiple round lasso to select stable feature
lasso.cv.select.feature(
data.matrix,
label,
folds = 5,
seed = 666,
n = 100,
family = "binomial",
type.measure = "auc",
cores = 50,
scale = TRUE
)
data.matrix |
Row is sample |
n |
100 |
family |
Default binomial |
type.measure |
Default auc. Can be class, auc, deviance, mae. “deviance” uses actual deviance. “mae” uses mean absolute error. “class” gives misclassification error. “auc” (for two-class logistic regression ONLY) gives area under the ROC curve. |
cores |
50 |
scale |
Default TRUE |
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