Preprocessing powertransformeroptions

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PowerTransformerOptions

Which power family PowerTransformer fits, and whether it standardises after.

public sealed record PowerTransformerOptions

Properties — Method is which family; scikit-learn's method, default PowerMethod.YeoJohnson. Standardize centres and scales the transformed column; standardize, default true.

Example — turning the standardisation off leaves the raw power.

using Lodestar.Preprocessing;

double[] income = [22.0, 25.0, 28.0, 31.0, 35.0, 42.0, 55.0, 78.0, 120.0, 260.0];

var options = new PowerTransformerOptions { Standardize = false };

PowerTransformer raw = PowerTransformer.Fit(income, 1, options);

double[] ends = raw.Transform([22.0, 260.0]);

double smallest = Math.Round(ends[0], 4);   // => 1.1403
double largest = Math.Round(ends[1], 4);    // => 1.225

Remarks — Standardize changes the output, never the exponent. The likelihood is maximised on the powered column before anything is centred, so both settings fit the same Lambdas; the switch decides only whether the mean and the population deviation of that column are divided out afterwards.

Leave it on unless something downstream needs the raw scale. The powered values above span 1.14 to 1.23, a range that will disappear beside any unscaled neighbour in the same matrix — which is the reason the reference defaults it on.

copy is absent, as everywhere in this package.

Being a record, two option sets with the same two values are equal.

Applies to — net10.0, netstandard2.0.

See also — PowerTransformer.Fit, PowerMethod.