Selects endmember candidates by projecting the data onto randomly generated
vectors and identifying extreme points in the projected space.
random_projections(data, p, iter_max = 2 * p)
Arguments
- data
A numeric matrix where each row represents a data point and each column
represents a coordinate/dimension.
- p
Number of endmembers to select.
- iter_max
Maximum number of projections to try, to avoid edge cases where
all (or many) projections result in same extreme points.
Value
A list containing:
- indices
An integer vector of length p containing the row indices of
the selected endmember candidates from the input data matrix.
Examples
# Create sample data
set.seed(123)
data("demo_data")
# Select 4 endmembers using random projections
result <- random_projections(demo_data, p=4)
print(result$indices)
#> [1] 9 3 7 2