Metric for Matrix-Wise Accuracy

Computes the matrix-wise accuracy.

metric_matrix_wise(estimate, oracle, na.rm = FALSE)

Arguments

estimate	Estimated values from the model.
oracle	Known values used to generate the model.
na.rm	A logical indicating if missing values (including NaN) should be removed. Default: FALSE

Value

A single numeric value between 0 and 1.

Details

The matrix-wise metric is a variant of accuracy that holistically looks at the entire estimated matrix against the entire

The metric is computed under: $$I(\hat{\theta}=\theta)$$

Recovery Use

The element-wise recovery metric is best used to understand differences between dichotomous matrices such as the \(\boldsymbol{Q}\) and \(\boldsymbol{\Delta}\) matrices.

See also

base::norm()

Examples

# Construct data
estimate = matrix(c(1,1,2,4,3,6), nrow = 2, ncol = 3)
truth = matrix(c(1,2,3,4,5,6), nrow = 2, ncol = 3)

# Compute the frobenius norm
metric_matrix_wise(estimate, truth)
#> [1] 0