DBSCAN density-based clustering (R parity)

Wraps dbscan::dbscan.

Usage

morie_dbscan_clustering(x, eps = 0.5, min_samples = 5L, metric = "euclidean")

Arguments

x

Numeric matrix.

eps

Neighbourhood radius.

min_samples

Minimum points in eps-neighbourhood for a core point.

metric

Distance metric (passed to dbscan).

Value

Named list: estimate, labels, n_clusters, n_noise, core_sample_indices, eps, min_samples, n, method.

Examples

morie_dbscan_clustering(x = rnorm(50))
#> $estimate
#> [1] 1
#> 
#> $labels
#>  [1]  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0 -1  0  0  0  0  0  0  0  0
#> [26]  0  0  0  0  0  0  0  0  0  0 -1  0  0  0  0  0 -1  0  0  0  0  0  0  0  0
#> 
#> $n_clusters
#> [1] 1
#> 
#> $n_noise
#> [1] 3
#> 
#> $core_sample_indices
#>  [1]  0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 17 18 19 20 21 22 23 24 25
#> [26] 26 27 28 29 30 31 32 33 34 36 37 38 39 40 42 43 44 45 46 47 48 49
#> 
#> $eps
#> [1] 0.5
#> 
#> $min_samples
#> [1] 5
#> 
#> $n
#> [1] 50
#> 
#> $method
#> [1] "DBSCAN (Ester et al. 1996)"
#>