/// <summary>
/// Predict a target using a linear binary classification model trained with the <see cref="SymbolicSgdTrainer"/>.
/// Stochastic gradient descent (SGD) is an iterative algorithm that optimizes a differentiable objective function.
/// The <see cref="SymbolicSgdTrainer"/> parallelizes SGD using <a href="https://www.microsoft.com/en-us/research/project/project-parade/#!symbolic-execution">symbolic execution</a>.
/// </summary>
/// <param name="catalog">The <see cref="BinaryClassificationCatalog"/>.</param>
/// <param name="options">Algorithm advanced options. See <see cref="SymbolicSgdTrainer.Options"/>.</param>
/// <example>
/// <format type="text/markdown">
/// <]
/// ]]>
/// </format>
/// </example>
public static SymbolicSgdTrainer SymbolicSgd(
this BinaryClassificationCatalog.BinaryClassificationTrainers catalog,
SymbolicSgdTrainer.Options options)
{
Contracts.CheckValue(catalog, nameof(catalog));
Contracts.CheckValue(options, nameof(options));
var env = CatalogUtils.GetEnvironment(catalog);
return(new SymbolicSgdTrainer(env, options));
}
/// <summary>
/// Predict a target using a linear binary classification model trained with the <see cref="SymbolicSgdTrainer"/>.
/// Stochastic gradient descent (SGD) is an iterative algorithm that optimizes a differentiable objective function.
/// The <see cref="SymbolicSgdTrainer"/> parallelizes SGD using <a href="https://www.microsoft.com/en-us/research/project/project-parade/#!symbolic-execution">symbolic execution</a>.
/// </summary>
/// <param name="catalog">The <see cref="BinaryClassificationCatalog"/>.</param>
/// <param name="labelColumnName">The name of the label column.</param>
/// <param name="featureColumnName">The name of the feature column.</param>
/// <param name="numberOfIterations">Number of training iterations.</param>
/// <example>
/// <format type="text/markdown">
/// <]
/// ]]>
/// </format>
/// </example>
public static SymbolicSgdTrainer SymbolicSgd(this BinaryClassificationCatalog.BinaryClassificationTrainers catalog,
string labelColumnName = DefaultColumnNames.Label,
string featureColumnName = DefaultColumnNames.Features,
int numberOfIterations = SymbolicSgdTrainer.Defaults.NumberOfIterations)
{
Contracts.CheckValue(catalog, nameof(catalog));
var env = CatalogUtils.GetEnvironment(catalog);
var options = new SymbolicSgdTrainer.Options
{
LabelColumnName = labelColumnName,
FeatureColumnName = featureColumnName,
};
return(new SymbolicSgdTrainer(env, options));
}
