/// <summary>
/// Trains an arbitrary number of models on the
/// provided examples by creating a separation
/// of data based on training percentage. Each generator
/// is rerun a predetermined amount of times.
/// </summary>
/// <param name="examples">Source data</param>
/// <param name="trainingPercentage">Data split percentage</param>
/// <param name="repeat">Number of repetitions per generator</param>
/// <param name="generators">Model generators used</param>
/// <returns>Best models for each generator</returns>
public static LearningModel[] Learn(IEnumerable<object> examples, double trainingPercentage, int repeat, params IGenerator[] generators)
{
if (generators.Length == 0)
throw new InvalidOperationException("Need to have at least one generator!");
// set up models
var models = new LearningModel[generators.Length];
for (int i = 0; i < generators.Length; i++)
models[i] = Learn(examples, trainingPercentage, repeat, generators[i]);
return models;
}
