smoothing_quantization: Smoothing by quantization (k-means)
In daltoolbox: Leveraging Experiment Lines to Data Analytics

View source: R/trans_smoothing_quantization.R

smoothing_quantization

R Documentation

Smoothing by quantization (k-means)

Description

Quantize a numeric vector into n levels using k‑means on the values and replace each value by its cluster mean (vector quantization).

Usage

smoothing_quantization(n)

Arguments

`n`	number of bins

Value

returns an object of class smoothing_quantization

References

MacQueen, J. (1967). Some Methods for classification and Analysis of Multivariate Observations.

Examples

data(iris)
obj <- smoothing_quantization(n = 2)
obj <- fit(obj, iris$Sepal.Length)
sl.bi <- transform(obj, iris$Sepal.Length)
table(sl.bi)
obj$interval

bins <- cut(iris$Sepal.Length, unique(obj$interval.adj), FALSE, include.lowest = TRUE)
entro <- evaluate(obj, bins, iris$Species)
entro$entropy

daltoolbox documentation built on May 14, 2026, 9:06 a.m.