trainstepC {DatabionicSwarm}

internal function for s-esom

Description

Does the training for fixed bestmatches in one epoch of the sESOM.

Usage

trainstepC(vx,vy, DataSampled,BMUsampled,Lines,Columns, Radius, toroid, NoCases)

Arguments

vx

array [1:Lines,1:Columns,1:Weights], WeightVectors that will be trained, internally transformed von NumericVector to cube

vy

array [1:Lines,1:Columns,1:2], meshgrid for output distance computation

DataSampled

NumericMatrix, n cases shuffled Dataset[1:n,1:d] by sample

BMUsampled

NumericMatrix, n cases shuffled BestMatches[1:n,1:2] by sample in the same way as DataSampled

Lines

double, Height of the grid

Columns

double, Width of the grid

Radius

double, The current Radius that should be used to define neighbours to the bm

toroid

bool, Should the grid be considered with cyclically connected borders?

NoCases

int, number of samples in the given non-sampled dataset

Details

Algorithm is described in [Thrun, 2018, p. 48, Listing 5.1].

Value

WeightVectors, array[1:Lines,1:Columns,1:weights] with the adjusted Weights

Note

Usually not for seperated usage!

Author(s)

Michael Thrun

References

[Thrun, 2018] Thrun, M. C.: Projection Based Clustering through Self-Organization and Swarm Intelligence, doctoral dissertation 2017, Springer, Heidelberg, ISBN: 978-3-658-20539-3, doi:10.1007/978-3-658-20540-9, 2018.