Metrics are functions that tell how much information would be
lost for a given reduction in the data. reduce. as_measure() is a
helper function to create new metrics to be used in partitioners.
partitioners can be created with as_partitioner().
measure_min_icc() assesses information loss by calculating the
intraclass correlation coefficient for each set of the target variables and
finding their minimum.
measure_min_icc(.partition_step, search_method = c("binary", "linear"))a partition_step object
The search method. Binary search is generally more efficient but linear search can be faster in very low dimensions.
a partition_step object
Other metrics: as_measure,
measure_icc, measure_min_r2,
measure_std_mutualinfo,
measure_variance_explained