find_outmost_points {archetypal} | R Documentation |
Function which finds the outermost points in order to be used as initial solution in archetypal analysis
Description
Function which finds the outermost points in order to be used as initial solution in archetypal analysis
Usage
find_outmost_points(df, kappas)
Arguments
df |
The data frame with dimensions n x d |
kappas |
The number of archetypes |
Value
A list with members:
outmost, the first kappas most frequent outermost points as rows of data frame
outmostall, all the outermost points that have been found as rows of data frame
outmostfrequency, a matrix with frequency and cumulative frequency for outermost rows
Warning
This is a rather naive way to find the outermost points of a data frame and it should be used with caution since for a n x d matrix we need in general 8 n^2/(2^30) GB RAM for numeric case. Check your machine and use it. As a rule of thumb we advice its usage for n less or equal than 20000.
See Also
find_furthestsum_points
, find_outmost_convexhull_points
,
find_outmost_projected_convexhull_points
,
and find_outmost_partitioned_convexhull_points
Examples
data("wd2") #2D demo
df = wd2
yy = find_outmost_points(df,kappas=3)
yy$outmost #the rows of 3 outmost points
yy$outmostall #all outmost found
yy$outmostfrequency #frequency table for all
df[yy$outmost,] #the 3 outmost points
#
###
#
data("wd3") #3D demo
df = wd3
yy = find_outmost_points(df,kappas=4)
yy$outmost #the rows of 4 outmost points
yy$outmostall #all outmost found
yy$outmostfrequency #frequency table for all
df[yy$outmost,] #the 4 outmost points