When evaluating the performance of a keras
model, these are the available metrics
For regression, I would however like to use e.g. pearson
or spearman
, such that:
set.seed(13985)
n_dps = 100
y_pred = runif(n_dps)
y_true = runif(n_dps)
pcc = cor(x = y_pred, y = y_true, method = "pearson")
scc = cor(x = y_pred, y = y_true, method = "spearman")
> pcc
[1] 0.04832645
> scc
[1] 0.09146115
I can't really seem to find a good example on how to do this - Any pointers would be appreciated