| part_minr2 {partition} | R Documentation |
Partitioner: distance, minimum R-squared, scaled means
Description
Partitioners are functions that tell the partition algorithm 1)
what to try to reduce 2) how to measure how much information is lost from
the reduction and 3) how to reduce the data. In partition, functions that
handle 1) are called directors, functions that handle 2) are called
metrics, and functions that handle 3) are called reducers. partition has a
number of pre-specified partitioners for agglomerative data reduction.
Custom partitioners can be created with as_partitioner().
Pass partitioner objects to the partitioner argument of partition().
part_minr2() uses the following direct-measure-reduce approach:
-
direct:
direct_distance(), Minimum Distance -
measure:
measure_min_r2(), Minimum R-Squared -
reduce:
reduce_scaled_mean(), Scaled Row Means
Usage
part_minr2(spearman = FALSE)
Arguments
spearman |
logical. Use Spearman's correlation for distance matrix? |
Value
a partitioner
See Also
Other partitioners:
as_partitioner(),
part_icc(),
part_kmeans(),
part_pc1(),
part_stdmi(),
replace_partitioner()
Examples
set.seed(123)
df <- simulate_block_data(c(3, 4, 5), lower_corr = .4, upper_corr = .6, n = 100)
# fit partition using part_minr2()
partition(df, threshold = .6, partitioner = part_minr2())