THIS PACKAGE HAS BEEN SUPERSEDED BY DISCRETIZERS.jl

This package supports discretization methods and mapping functions.

• LabelMaps map between discrete values

• BinMaps map from continuous values to corresponding bins

• DataLabelMaps and DataBinMaps support NA values

Construct a binmap type mapping floats to Uint8 bin indeces:

bin_edges = [0.0, 0.5, 1.0, 2.0]
bmap = binmap(bin_edges, Uint8)
nlabels(bmap) -> 3

The primary interface is encoding and decoding:

encode(bmap, 0.25) -> 0x01
encode(bmap, [0.2, 1.5, 0.2]) -> [0x01, 0x02, 0x01]
decode(bmap, uint8(1)) -> rand(0.0:0.5)

BinMaps supports several binning algorithms, including:

• uniform width discretization
• uniform sample count discretization
• MODL bayes-optimal binning for continuous features over a discrete target

bin_edges = binedges(DISCRETIZE_UNIFORMWIDTH, 2, [0.0, 0.2, 0.1, 1.0, 0.6])
  -> [0.0, 0.5, 1.0]

For questions please contact the package creator or create an issue

Feel free to create pull requests to improve the package