Preprocessing kbinsdiscretizer transform

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KBinsDiscretizer.Transform

Reads each value as the bin it falls in.

public double[] Transform(ReadOnlySpan<double> samples)

Parameters — samples is the matrix to transform, row-major, FeatureCount values per row.

Returns — a new matrix, OutputFeatureCount values per row: the bin's index under BinEncoding.Ordinal, or one column per bin of each feature with exactly one of them set under OneHot.

Exceptions — ArgumentException when samples holds a partial row or a non-finite value.

Example — one age, one-hot across four bins.

using Lodestar.Preprocessing;

double[] ages = [19.0, 22.0, 25.0, 31.0, 38.0, 44.0, 52.0, 61.0, 67.0, 74.0];

KBinsDiscretizer bins = KBinsDiscretizer.Fit(
    ages, 1, new KBinsDiscretizerOptions { BinCount = 4 });

int width = bins.OutputFeatureCount;                        // => 4
string row = string.Join(",", bins.Transform([44.0]));      // => 0,0,1,0

Remarks — a value outside the fitted range is clamped, not refused. Anything below the first edge lands in bin 0 and anything above the last in the last bin, which is the reference's behaviour: the edges describe where the fitted data was, and a later row is allowed to be outside it.

The one-hot layout is per feature, concatenated. Three features with four, two and five bins give an eleven-column row whose blocks start at 0, 4 and 6 — so a caller reading a particular feature's block needs the running sum of BinCounts, not feature × BinCount, because a feature can end with fewer bins than it asked for.

Applies to — net10.0, netstandard2.0.

See also — KBinsDiscretizer.Fit, KBinsDiscretizer.InverseTransform, BinEncoding.