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Train FieldAwareFactorizationMachines without providing arguments #2931

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merged 6 commits into from
Mar 13, 2019
Merged

Train FieldAwareFactorizationMachines without providing arguments #2931

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f233c90
Adding an option to provide FM with an empty arguments list.
Mar 12, 2019
dbcd0f0
Update the doc strings
Mar 12, 2019
2b12747
Update the doc strings
Mar 12, 2019
5fd2e6c
Addressing PR Comments
Mar 13, 2019
fe892c0
Merge branch 'master' into 2927_fm_empty_args
Mar 13, 2019
14a46f0
Fixing breaking changes in master.
Mar 13, 2019
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23 changes: 23 additions & 0 deletions src/Microsoft.ML.StandardTrainers/FactorizationMachine/FactorizationMachineCatalog.cs
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Expand Up @@ -13,6 +13,29 @@ namespace Microsoft.ML
/// </summary>
public static class FactorizationMachineExtensions
{
/// <summary>
/// Predict a target using a field-aware factorization machine algorithm.
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@wschin wschin Mar 12, 2019 •
edited by rogancarr
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Please add Note that because there is only one feature column, the underlying model is equivalent to standard factorization machine. #Resolved

/// </summary>
/// <param name="catalog">The binary classification catalog trainer object.</param>
/// <param name="featureColumnName">The name of the feature column.</param>
/// <param name="labelColumnName">The name of the label column.</param>
/// <param name="exampleWeightColumnName">The name of the example weight column (optional).</param>
/// <example>
/// <format type="text/markdown">
/// <![CDATA[
/// [!code-csharp[FieldAwareFactorizationMachine](~/../docs/samples/docs/samples/Microsoft.ML.Samples/Dynamic/Trainers/BinaryClassification/FieldAwareFactorizationMachine.cs)]
/// ]]></format>
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@sfilipi sfilipi Mar 13, 2019 •
edited by rogancarr
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Does this sample illustrate this API, or one of the other ones below? This first one and the second are failry similar, but the third API is a bit different; idk if it will get confusing. #Resolved

/// </example>
public static FieldAwareFactorizationMachineBinaryClassificationTrainer FieldAwareFactorizationMachine(this BinaryClassificationCatalog.BinaryClassificationTrainers catalog,
string featureColumnName = DefaultColumnNames.Features,
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@wschin wschin Mar 12, 2019 •
edited by rogancarr
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A test please. #Resolved

string labelColumnName = DefaultColumnNames.Label,
string exampleWeightColumnName = null)
{
Contracts.CheckValue(catalog, nameof(catalog));
var env = CatalogUtils.GetEnvironment(catalog);
return new FieldAwareFactorizationMachineBinaryClassificationTrainer(env, new string[] { featureColumnName }, labelColumnName, exampleWeightColumnName);
}

/// <summary>
/// Predict a target using a field-aware factorization machine algorithm.
/// </summary>
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