The parameter descriptions should distinguish between columns and column names.

[sfilipi]

As @wschin pointed out here: #2170 (comment) the parmaters, and in general our XML documentation should distinguish between columns and column names.

This issue will be considered closed when all the params of this language:

/// <param name="labelColumn">The label column.</param>
/// <param name="featureColumn">The featureColumn column.</param>
/// <param name="weights">The optional weights column.</param>

Get changed to:

/// <param name="labelColumnName">The name of the label column.</param>
/// <param name="featureColumnName">The name of the feature column.</param>
/// <param name="weightsColumnName">The name of the optional weights column.</param>

[glebuk]

Should the weights be renamed to weightsColumn, or perhaps exampleWeightsColumn?

[HerraHak]

How can we contribute on this issue?

[abgoswam]

@sfilipi .

For most of the learners, the feature column name is a string

machinelearning/src/Microsoft.ML.HalLearners/HalLearnersCatalog.cs

Lines 31 to 34 in 4a71e50

	public static OlsLinearRegressionTrainer OrdinaryLeastSquares(this RegressionCatalog.RegressionTrainers catalog,
	string labelColumnName = DefaultColumnNames.Label,
	string featureColumnName = DefaultColumnNames.Features,
	string weightColumn = null)

But for FactorizationMachine, the features column is a string[]

machinelearning/src/Microsoft.ML.StandardLearners/FactorizationMachine/FactorizationMachineCatalog.cs

Lines 29 to 32 in 4a71e50

	public static FieldAwareFactorizationMachineTrainer FieldAwareFactorizationMachine(this BinaryClassificationCatalog.BinaryClassificationTrainers catalog,
	string[] featureColumns,
	string labelColumn = DefaultColumnNames.Label,
	string weights = null)

So would we treat FactorizationMachine as an aberration ?

@Ivanidzo4ka @glebuk