postResample is meant to be used with
apply across a matrix. For numeric data
the code checks to see if the standard deviation of either vector is zero. If so, the correlation
between those samples is assigned a value of zero.
NA values are ignored everywhere.
Note that many models have more predictors (or parameters) than data points, so the typical mean squared
error denominator (n - p) does not apply. Root mean squared error is calculated using
sqrt(mean((pred - obs)^2.
Also, R-squared is calculated as the square of the correlation between the observed and predicted outcomes.
defaultSummary is the default function to compute performance metrics in
train. It is a wrapper around
Other functions can be used via the
summaryFunction argument of
trainControl. Custom functions must have the same arguments as