> library(dbscan)
バージョン: 1.1.1
| . |
| DS3 DS3: Spatial data with arbitrary shapes |
| NN Nearest Neighbors Auxiliary Functions |
| dbscan DBSCAN |
| extractFOSC Framework for Optimal Selection of Clusters |
| frNN Find the Fixed Radius Nearest Neighbors |
| glosh Global-Local Outlier Score from Hierarchies |
| hdbscan HDBSCAN |
| hullplot Plot Convex Hulls of Clusters |
| jpclust Jarvis-Patrick Clustering |
| kNN Find the k Nearest Neighbors |
| kNNdist Calculate and plot the k-Nearest Neighbor |
| Distance |
| lof Local Outlier Factor Score |
| moons Moons Data |
| optics OPTICS |
| pointdensity Calculate Local Density at Each Data Point |
| reachability Density Reachability Structures |
| sNN Shared Nearest Neighbors |
| sNNclust Shared Nearest Neighbor Clustering |
| 関数名 |
概略 |
dbscan |
DBSCAN |
frNN |
Find the Fixed Radius Nearest Neighbors |
hullplot |
Plot Convex Hulls of Clusters |
jpclust |
Jarvis-Patrick Clustering |
kNN |
Find the k Nearest Neighbors |
kNNdist |
Calculate and plot the k-Nearest Neighbor Distance |
lof |
Local Outlier Factor Score |
optics |
OPTICS |
reachability |
Density Reachability Structures |
> set.seed(71)
> n <- 100
> x <- cbind(
+ x = runif(10, 0, 10) + rnorm(n, sd = 0.2),
+ y = runif(10, 0, 10) + rnorm(n, sd = 0.2)
+ )
>
> (res <- dbscan(x, eps = .3, minPts = 3))
DBSCAN clustering for 100 objects.
Parameters: eps = 0.3, minPts = 3
The clustering contains 9 cluster(s) and 11 noise points.
0 1 2 3 4 5 6 7 8 9
11 20 10 10 10 8 8 4 9 10
Available fields: cluster, eps, minPts