Class demo scaling techniques

scaling.R

min_max <- function(x, ...) {
    m <- min(x, na.rm = TRUE)
    (x - m)/(max(x, na.rm = TRUE) - m)
}

standardization <- function(x, ...) {
    
    if (length(stats::na.omit(unique(x))) > 1) {
        scale(x) 
    } else {
        rep(0, length(x))
    }
    
}

mean_normalization  <- function(x, ...) {

    (x - mean(x, na.rm = TRUE))/(max(x, na.rm = TRUE) - min(x, na.rm = TRUE))
}

lapply(list(
        normal = rnorm(1000, 10, 20),
        binary = rbinom(n=1000, size=1, prob=0.05),
        chisq_df3 = rchisq(1000, df =  3),
        chisq_df1 = rchisq(1000, df =  1),
        uniform = runif(10000)
    ), function(x){
        par(mfrow = c(2, 2), ask = TRUE)
        hist(x, main= 'unscaled')
        hist(min_max(x), main= 'min max')
        hist(standardization(x), main='standardization')
        hist(mean_normalization(x), main='mean normalization')
})