qkdbscan-class: Class "qkdbscan"

In qkerntool: Q-Kernel-Based and Conditionally Negative Definite Kernel-Based Machine Learning Tools

Description

The qkernel-DBSCAN class.

Objects of class "qkdbscan"

Objects can be created by calls of the form new("qkdbscan", ...). or by calling the qkdbscan function.

Slots

clust:

Object of class "vector" containing the cluster membership of the samples

eps:

Object of class "numeric" containing the reachability distance

MinPts:

Object of class "numeric" containing the reachability minimum number of points

isseed:

Object of class "logical" containing the logical vector indicating whether a point is a seed (not border, not noise)

Methods

clust

signature(object = "qkdbscan"): returns the cluster membership

kcall

signature(object = "qkdbscan"): returns the performed call

cndkernf

signature(object = "qkdbscan"): returns the used kernel function

eps

signature(object = "qkdbscan"): returns the reachability distance

MinPts

signature(object = "qkdbscan"): returns the reachability minimum number of points

predict

signature(object = "qkdbscan"): embeds new data

xmatrix

signature(object = "qkdbscan"): returns the used data matrix

Author(s)

Yusen Zhang
[e-mail]

See Also

qkernel-class, cndkernel-class

Examples

# a simple example using the iris data
x<- as.matrix(iris[,-5])
ds <- qkdbscan (x,kernel="laplbase",qpar=list(sigma=3.5,q=0.8),eps=0.15,
MinPts=5,hybrid = FALSE)
# print the results
clust(ds)
eps(ds)
MinPts(ds)
cndkernf(ds)
xmatrix(ds)
kcall(ds)

qkerntool documentation built on May 2, 2019, 6:11 a.m.