daltoolbox (version 1.3.767)

smoothing: Smoothing (binning/quantization)

Description

Family of smoothing methods that reduce noise by replacing values with the mean of a bin. Supported strategies include equal‑interval bins, equal‑frequency (quantile) bins, k-means quantization, and class-aware clustering.

Usage

smoothing(n)

Value

returns an object of class smoothing

Arguments

n

number of bins

Details

The smoothing level is controlled by n (number of bins/levels). The base helper tune() chooses n by locating the elbow (maximum curvature) of the MSE curve across candidates. Concrete subclasses may override that criterion when supervision is required. After fit(), values are mapped to bin means via transform().

Examples

data(iris)
obj <- smoothing_inter(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