Discretization — discretize • infoxtr

Discretize a numeric vector into categorical classes using several commonly used discretization methods. Missing values (NA/NaN) are ignored and returned as class 0.

Usage

discretize(
  x,
  n = 5,
  method = "natural",
  large = 3000,
  prop = 0.15,
  seed = 123456789,
  thr = 0.4,
  iter = 100,
  bps = NULL,
  right_closed = TRUE
)

Arguments

x: A vector.
n: (optional) Number of classes.
method: (optional) Discretization method. One of "sd", "equal", "geometric", "quantile", "manual", "natural("jenks")", or "headtail"("headtails").
large: (optional) Threshold sample size for natural breaks sampling.
prop: (optional) Sampling proportion used when method = "natural" and the input size exceeds large.
seed: (optional) Random seed used for sampling in natural breaks.
thr: (optional) Threshold used in the head/tail breaks algorithm.
iter: (optional) Maximum number of iterations for head/tail breaks.
bps: (optional) Numeric vector of manual breakpoints used when method = "manual".
right_closed: (optional) Logical. If TRUE, intervals are right-closed (e.g., (a, b]). If FALSE, intervals are left-closed [a, b).

Value

A discretized integer vector.

Note

If x is not numeric, it will be converted to integer categories via as.factor().

Examples

set.seed(42)
infoxtr::discretize(stats::rnorm(99,1,10))
#>  [1] 5 3 4 4 4 3 5 3 5 3 5 5 2 3 3 4 3 1 1 5 3 1 3 5 5 3 3 1 4 2 4 4 5 2 4 1 2 2
#> [39] 1 3 4 3 4 2 2 4 2 5 3 4 4 2 5 4 3 4 4 3 1 4 3 4 4 5 2 5 4 5 4 4 2 3 4 2 3 4
#> [77] 4 4 2 2 5 4 3 3 2 4 3 3 4 4 5 3 4 5 2 2 2 2 3