metalearner_convexcomb: Convex combination meta learner

In targeted: Targeted Inference

Convex combination meta learner

Description

Estimates the ensemble weights of a superlearner by minimizing the cross-validated MSE as a convex combination of the candidate predictions, i.e. by least squares regression of the response on the candidate predictions subject to the constraint that the weights are non-negative and sum to one.

Usage

metalearner_convexcomb(y, pred, ...)

Arguments

y	(numeric) Response vector.
pred	(matrix) Matrix of cross-validated predictions with one column per candidate learner.
...	Additional arguments (currently ignored).

Value

(numeric) Vector of ensemble weights, one element per column of pred.

See Also

superlearner learner_sl

targeted documentation built on July 15, 2026, 9:06 a.m.