/// <summary>
/// Trains a logistic regression model on a data table
/// </summary>
/// <param name="table">The training data</param>
/// <param name="lap">Linear algebra provider</param>
/// <param name="iterations">Number of iterations to train for</param>
/// <param name="learningRate">The learning rate</param>
/// <param name="lambda">Regularisation lambda</param>
/// <param name="costCallback">Optional callback that is called after each iteration with the current cost</param>
/// <returns>The trained model</returns>
public static LogisticRegression TrainLogisticRegression(this IDataTable table,
ILinearAlgebraProvider lap, int iterations, float learningRate, float lambda = 0.1f,
Func <float, bool> costCallback = null)
{
var trainer = table.CreateLogisticRegressionTrainer(lap);
return(trainer.GradientDescent(iterations, learningRate, lambda, costCallback));
}
