This function automatically select non-correlated metrics based on a Spearman rank correlation test. To do so, we start from the pair of the strongest correlated metrics. Since these two metrics can be linearly predicted with each other, one of these two metrics must be removed while selecting the other. We select the metric that has the lowest Spearman correlation coefficient with the other metrics that are not in the pair. We repeat this process until all metrics have their Spearman correlation coefficient below a threshold value (default = 0.7).

get.automated.spearman(dataset, metrics, spearman.threshold, verbose = F)

Arguments

dataset

a data frame for data

metrics

a characters or a vector of characters for independent variables

spearman.threshold

a numeric for a threshold of Spearman rank correlation test (default = 0.7)

verbose

TRUE for printing