R: Calculation of the optimal number of neighbours.

calc_k {lle} | R Documentation

## Calculation of the optimal number of neighbours.

### Description

Calculates of optimal number of neighbours by using the algorithm proposed by Kayo (see Ref.). Therefore the LLE alorithm is performed for every k-neighbourhood size.

### Usage

     calc_k(X, m, kmin=1, kmax=20, plotres=TRUE,
                      parallel=FALSE, cpus=2, iLLE=FALSE)

### Arguments

`X` | matrix object containing the input data.
`m` | intrinsic dimension of the data.
`kmin` | minimal value of k.
`kmax` | maximal value of k.
`plotres` | a logical values indicating wheather to plot the result.
`parallel` | a logical values indicating wheather to use parallel computation on multiple cpu cores. See snowfall.
`cpus` | number of cpus cores used for parallel computation.
`iLLE` | a logical values indicating wheater to use improved LLE (very CPU intensive). See `lle`.

### Details

Since the calculation of the optimal number of neighbours m is a step that is normally applied before the execution of LLE itself, the intrinsic dimension may be unknown. In this case, a good guess is sufficient. If no good estimation can be made the largest plausible value should be chosen.

### Value

`res` | dataframe containing the number of neighbours and the calculated parameter ρ. The number of neighbours belonging to the smallest value of ρ should be chosen.

### References

Locally linear embedding algorithm - extensions and applications / Olga Kayo / Universitatis Ouluensis, Oulu, Finland / 2006

### Examples

       ## Not run:
    	data( lle_scurve_data )
    	X <- lle_scurve_data
    	calc_k( X, 2, 1, 15 )

    	data( lle_scurve_data )
    	X <- lle_scurve_data
    	calc_k( X, 2, 1, 15, FALSE, TRUE, 4 )

    ## End(Not run)

[Package lle version 1.1 Index]