trainstepC2: internal function for s-esom

In DatabionicSwarm: Swarm Intelligence for Self-Organized Clustering

internal function for s-esom

Description

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

Usage

trainstepC2(esomwts,aux, DataSampled,BMUsampled,Lines,Columns, Weights, Radius,
toroid, NoCases)

Arguments

esomwts	array [1:Lines,1:Columns,1:Weights], WeightVectors that will be trained, internally transformed von NumericVector to cube
aux	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
Weights	double, number of weights
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, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1007/978-3-658-20540-9")}, 2018.

DatabionicSwarm documentation built on June 22, 2024, 9:41 a.m.