getLambda {clusterHD}

select lambda based on AIC or BIC

Description

Select the regularization parameter for HTK-means clustering based on information criteria.

Usage

getLambda(HTKmeans.out, type  = "AIC")

Arguments

HTKmeans.out

the output of a call to HTKmeans.

type

either "AIC" (default) or "BIC".

Details

This function selects the best lambda (based on information criteria AIC or BIC) out of the HTKmeans.out$inputargs$lambdas sequence of values.

Value

The selected value for lambda

Author(s)

J. Raymaekers and R.H. Zamar

References

Raymaekers, Jakob, and Ruben H. Zamar. "Regularized K-means through hard-thresholding." arXiv preprint arXiv:2010.00950 (2020).

See Also

HTKmeans

Examples

X <- mclust::banknote
y <- as.numeric(as.factor(X[, 1]))
lambdas <- seq(0, 1, by = 0.01)
X <- X[, -1]
HTKmeans.out <- HTKmeans(X, 2, lambdas)

# Both AIC and BIC suggest a lambda of 0.02 here:


getLambda(HTKmeans.out, "AIC")
getLambda(HTKmeans.out, "BIC")