/// <summary>
/// Construct the LMA object.
/// </summary>
/// <param name="network">The network to train. Must have a single output neuron.</param>
/// <param name="training">The training data to use. Must be indexable.</param>
/// <param name="h">The Hessian calculator to use.</param>
public LevenbergMarquardtTraining(BasicNetwork network,
IMLDataSet training, IComputeHessian h)
: base(TrainingImplementationType.Iterative)
{
ValidateNetwork.ValidateMethodToData(network, training);
Training = training;
_indexableTraining = Training;
this._network = network;
_trainingLength = (int)_indexableTraining.Count;
_weightCount = this._network.Structure.CalculateSize();
_lambda = 0.1;
_deltas = new double[_weightCount];
_diagonal = new double[_weightCount];
var input = new BasicMLData(
_indexableTraining.InputSize);
var ideal = new BasicMLData(
_indexableTraining.IdealSize);
_pair = new BasicMLDataPair(input, ideal);
_hessian = h;
_hessian.Init(network, training);
}
/// <summary>
/// Construct the LMA object.
/// </summary>
/// <param name="network">The network to train. Must have a single output neuron.</param>
/// <param name="training">The training data to use. Must be indexable.</param>
/// <param name="h">The Hessian calculator to use.</param>
public LevenbergMarquardtTraining(BasicNetwork network,
IMLDataSet training, IComputeHessian h)
: base(TrainingImplementationType.Iterative)
{
ValidateNetwork.ValidateMethodToData(network, training);
Training = training;
_indexableTraining = Training;
_network = network;
_trainingLength = _indexableTraining.Count;
_weightCount = _network.Structure.CalculateSize();
_lambda = 0.1;
_deltas = new double[_weightCount];
_diagonal = new double[_weightCount];
_hessian = h;
}
/// <summary>
/// Construct the LMA object.
/// </summary>
/// <param name="network">The network to train. Must have a single output neuron.</param>
/// <param name="training"></param>
/// <param name="h">The training data to use. Must be indexable.</param>
public LevenbergMarquardtTraining(BasicNetwork network,
IMLDataSet training, IComputeHessian h)
: base(TrainingImplementationType.Iterative)
{
ValidateNetwork.ValidateMethodToData(network, training);
Training = training;
_indexableTraining = Training;
this._network = network;
_trainingLength = _indexableTraining.Count;
_weightCount = this._network.Structure.CalculateSize();
_lambda = 0.1;
_deltas = new double[_weightCount];
_diagonal = new double[_weightCount];
var input = new BasicMLData(
_indexableTraining.InputSize);
var ideal = new BasicMLData(
_indexableTraining.IdealSize);
_pair = new BasicMLDataPair(input, ideal);
_hessian = h;
}
