/// <summary>
/// Predict a target using a linear binary classification model trained with the <see cref="SymSgdClassificationTrainer"/>.
/// </summary>
/// <param name="catalog">The <see cref="BinaryClassificationCatalog"/>.</param>
/// <param name="options">Algorithm advanced options. See <see cref="SymSgdClassificationTrainer.Options"/>.</param>
public static SymSgdClassificationTrainer SymbolicStochasticGradientDescent(
this BinaryClassificationCatalog.BinaryClassificationTrainers catalog,
SymSgdClassificationTrainer.Options options)
{
Contracts.CheckValue(catalog, nameof(catalog));
Contracts.CheckValue(options, nameof(options));
var env = CatalogUtils.GetEnvironment(catalog);
return(new SymSgdClassificationTrainer(env, options));
}
/// <summary>
/// Predict a target using a linear binary classification model trained with the <see cref="SymSgdClassificationTrainer"/>.
/// </summary>
/// <param name="catalog">The <see cref="BinaryClassificationCatalog"/>.</param>
/// <param name="labelColumn">The labelColumn column.</param>
/// <param name="featureColumn">The features column.</param>
public static SymSgdClassificationTrainer SymbolicStochasticGradientDescent(this BinaryClassificationCatalog.BinaryClassificationTrainers catalog,
string labelColumn = DefaultColumnNames.Label,
string featureColumn = DefaultColumnNames.Features)
{
Contracts.CheckValue(catalog, nameof(catalog));
var env = CatalogUtils.GetEnvironment(catalog);
var options = new SymSgdClassificationTrainer.Options
{
LabelColumn = labelColumn,
FeatureColumn = featureColumn,
};
return(new SymSgdClassificationTrainer(env, options));
}
