Computes the element-wise accuracy of matrices.
metric_element_wise(estimate, oracle, na.rm = FALSE)
| estimate | Estimated values from the model. |
|---|---|
| oracle | Known values used to generate the model. |
| na.rm | A |
A single numeric value between 0 and 1.
The element-wise metric is also known as accuracy or the proportion of estimated values that are equivalent to the same elements in the oracle value.
The metric is computed under: $$\frac{1}{JK}\sum _{j=1}^J\sum _{k=1}^K\mathcal I(\hat{\theta}_{jk}=\theta_{jk})$$
The element-wise recovery metric is best used to understand differences between dichotomous matrices such as the \(\boldsymbol{Q}\) and \(\boldsymbol{\Delta}\) matrices.
# 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_element_wise(estimate, truth)#> [1] 0.5