Description Usage Arguments Value
Get outcome weights based on cross-validated super learner fits
1 2 | get_y_weight(task, Y, V, Ynames, all_fits, all_sl, all_fit_tasks,
sl_control, y_weight_control, folds, learners)
|
task |
A named list identifying what training folds to use to obtain outcome weights. |
Y |
A matrix or data.frame of outcomes |
V |
Number of outer folds of cross-validation (nested cross-validation uses V-1 and V-2 folds), so must be at least four. |
Ynames |
Names of the columns of |
all_fits |
A list of all learner fits (from |
all_sl |
A list of all super learner fits (from |
all_fit_tasks |
A list of all learner fitting tasks (quicker to search over
than |
sl_control |
A list with named entries ensemble.fn, optim_risk_fn, weight_fn,
cv_risk_fn, family. Available functions can be viewed with |
y_weight_control |
A list with named entries ensemble.fn, optim_risk_fn, weight_fn,
cv_risk_fn. Available functions can be viewed with |
folds |
Vector identifying which fold observations fall into. |
learners |
Super learner wrappers. See |
Named list identifying training folds used and the composite outcome weights.
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