get_voronoi_feature {MaxWiK} | R Documentation |
The function to get feature representation in RKHS based on Voronoi diagram for WHOLE dataset
Description
The function to get feature representation in RKHS based on Voronoi diagram for WHOLE dataset
Usage
get_voronoi_feature(
psi = 40,
t = 350,
data,
talkative = FALSE,
Matrix_Voronoi = NULL
)
add_new_point_iKernel(data, d1, Matrix_Voronoi, dissim, t, psi, nr)
Arguments
psi |
Integer number related to the size of each Voronoi diagram |
t |
Integer number of trees in Isolation Kernel or dimension of RKHS |
data |
dataset of points, rows - points, columns - dimensions of a point |
talkative |
logical. If TRUE then print messages, FALSE for the silent execution |
Matrix_Voronoi |
Matrix of Voronoi diagrams, if it is NULL then the function will calculate Matrix_Voronoi |
d1 |
Data point - usually it is an observation data point |
dissim |
Matrix of dissimilarity or distances between all points. |
nr |
Integer number of rows in matrix of distances (dissim) and also the size of dataset |
Value
Feature representation in RKHS based on Voronoi diagram for WHOLE dataset
RKHS mapping for a new point based on Isolation Kernel mapping
Functions
-
add_new_point_iKernel()
: The function to get RKHS mapping based on Isolation Kernel for a new point
Examples
NULL
NULL