Description Usage Arguments Value See Also
Using the spams toolbox to run group lasso at various parameters to identify parameter combination with best test auc.
1 2 3 | group.lasso.eval.parameters(train.features, train.labels, test.features,
test.labels, groups, lambdas = c(0.01, 0.005, 0.001, 5e-04, 1e-04),
no.cores = 1)
|
train.features |
Training feature matrix |
train.labels |
Training labels (Should be +1/-1) |
test.features |
Test feature matrix |
test.labels |
Test labels (Should be +1/-1) |
groups |
Feature assignment to groups. Each feature should belong to exactly one group |
lambdas |
Vector of regularization parameters |
no.cores |
Number of cores for parallel processing |
List containing lambdas
and a matrix of test aucs named auc.matrix
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