flexclust (version 1.3-4)

flexclustControl-class: Classes "flexclustControl" and "cclustControl"

Description

Hyperparameters for cluster algorithms.

Objects from the Class

Objects can be created by calls of the form new("flexclustControl", ...). In addition, named lists can be coerced to flexclustControl objects, names are completed if unique (see examples).

Learning Rate of Neural Gas

The neural gas algorithm uses updates of form $$cnew = cold + e*exp(-m/l)*(x - cold)$$ for every centroid, where $m$ is the order (minus 1) of the centroid with respect to distance to data point $x$ (0=closest, 1=second, ...). The parameters $e$ and $l$ are given by $$e = par1*(par2/par1)^(iter/iter.max),$$ $$l = par3*(par4/par3)^(iter/iter.max).$$ See Martinetz et al (1993) for details of the algorithm, and the examples section on how to obtain default values.

References

Martinetz T., Berkovich S., and Schulten K. (1993). "Neural-Gas Network for Vector Quantization and its Application to Time-Series Prediction." IEEE Transactions on Neural Networks, 4 (4), pp. 558--569.

Arthur D. and Vassilvitskii S. (2007). "k-means++: the advantages of careful seeding". Proceedings of the 18th annual ACM-SIAM symposium on Discrete algorithms. pp. 1027-1035.

See Also

kcca, cclust

Examples

## have a look at the defaults
new("flexclustControl")

## corce a list
mycont = list(iter=500, tol=0.001, class="w")
as(mycont, "flexclustControl")

## some additional slots
as(mycont, "cclustControl")

## default values for ng.rate
new("cclustControl")@ng.rate