VQ_codebookSplit: VQ_codebookSplit

In muHVT: Constructing Hierarchical Voronoi Tessellations and Overlay Heatmap for Data Analysis

VQ_codebookSplit

Description

Vector Quantization by codebook split method

Usage

VQ_codebookSplit(dataset, quant.err = 0.5, epsilon = NULL)

Arguments

dataset	Matrix. A matrix of multivariate data. Each row corresponds to an observation, and each column corresponds to a variable. Missing values are not accepted.
quant.err	Numeric. The quantization error for the algorithm.
epsilon	Numeric. The value to offset the codebooks during the codebook split. Default is NULL, in which case the value is set to quant.err parameter.

Details

Performs Vector Quantization by codebook split method. Initially, the entire dataset is considered to be one cluster where the codebook is the mean of the cluster. The quantization criteria is checked and the codebook is split such that the new codebooks are (codebook+epsilon) and (codebook-epsilon). The observations are reassigned to these new codebooks based on the nearest neighbour condition and the means recomputed for the new clusters. This is done iteratively until all the clusters meet the quantization criteria.

Value

clusters	List. A list showing each ID assigned to a cluster.
nodes.clust	List. A list corresponding to nodes' details.
idnodes	List. A list of ID and segments similar to nodes.clust with additional columns for nodes ID.
error.quant	List. A list of quantization error for all levels and nodes.
plt.clust	List. A list of logical values indicating if the quantization error was met.
summary	Summary. Output table with summary.

Author(s)

Sangeet Moy Das <[e-mail]>

See Also

hvtHmap

Examples

data("iris",package="datasets")
iris <- iris[,1:2]

vqOutput = VQ_codebookSplit(iris, quant.err = 0.5)

muHVT documentation built on March 7, 2023, 6:38 p.m.