find_weights: Calculate weight matrix.

Description Usage Arguments Value Examples

Description

Calculates the weights for every neighbour of x_i.

Usage

1
 find_weights(nns, X, m, reg = 2, ss = FALSE, p = 0.5, id = FALSE, v = 0.99) 

Arguments

nns

matrix of nearest neighbours using find_nn_k or find_nn_eps.

X

matrix object containing the input data.

m

intrinsic dimension of the data. See lle.

reg

regularisation method. See lle.

ss

a logical values indicating wheather to perform subset selection. See lle.

p

amount of data remaining after subset selection. See lle.

id

a logical values indicating wheather to calculate the intrinsic dimension. See lle.

v

threshold parameter for intrinsic dimension. See details.

Value

A list containing the following variables:

X

input data, can change if subset selection is applied

weights

weight matrix. If x_i is neighbour of x_j then -1<weights[i,j]<1, else zero.

choise

index vector of kept data while subset selection

id

additionally to the (optional) printed intrinsic dimension, the vector of intrinsic dimension for every data point is returned by the function, so that the vector can easily be ploted manually.

Examples

1
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3
4
	data( lle_scurve_data )
	X <- lle_scurve_data
	nns <- find_nn_k( X, 5 )
	weights <- find_weights( nns, X, 2, 2 )

Example output

Loading required package: scatterplot3d
Loading required package: MASS
Loading required package: snowfall
Loading required package: snow

lle documentation built on May 2, 2019, 2:49 p.m.