Development build. This page describes main, not a released package. The latest published Lodestar.Preprocessing is 0.2.0 — read its documentation.

Home › Preprocessing › Encoding and imputation

Fits a label encoder on one column of labels.

public static LabelEncoder<T> Label<T>(ReadOnlySpan<T> labels) where T : IComparable<T>, IEquatable<T>

Type parameter — T is the label type; string and int are the two the reference takes.

Parameters — labels is one column of labels.

Returns — a fitted LabelEncoder. Its classes are sorted. The order is numpy's: a string sorts by code point, not by UTF-16 unit (#1254), and a floating NaN sorts last (#1229).

Exceptions — ArgumentException when labels is empty or holds a null.

Example — the codes and how many rows were read.

using Lodestar.Preprocessing;

string[] cities = ["paris", "lyon", "paris", "nice"];

LabelEncoder<string> encoder = Encoders.Label<string>(cities);

int rows = encoder.SampleCount;                        // => 4
string classes = string.Join(",", encoder.Classes);    // => lyon,nice,paris

Remarks — one column, not a matrix, which is the one difference from Encoders.Ordinal: the reference's LabelEncoder takes a 1-D array and its OrdinalEncoder a 2-D one, because the first is for a target and the second for features. There is no featureCount parameter here for that reason.

Applies to — net10.0, netstandard2.0.

See also — LabelEncoder, Encoders, Encoders.Ordinal.