cram_var_expected_loss: Cram ML: Variance Estimate of the crammed expected loss...

In cramR: Cram Method for Efficient Simultaneous Learning and Evaluation

Cram ML: Variance Estimate of the crammed expected loss estimate

Description

This function computes the variance estimator based on the given loss matrix and batch indices.

Usage

cram_var_expected_loss(loss, batch_indices)

Arguments

loss	A matrix of loss values with N rows (data points) and K+1 columns (batches). We assume that the first column of the loss matrix contains only zeros. The following nb_batch columns contain the losses of each trained model for each individual.
batch_indices	A list where each element is a vector of indices corresponding to a batch.

Value

The variance estimate of the crammed expected loss estimate

cramR documentation built on Aug. 25, 2025, 1:12 a.m.