public StochasticGradientDescent(IContainsFlat network,
IMLDataSet training, IGenerateRandom theRandom) :
base(TrainingImplementationType.Iterative)
{
Training = training;
UpdateRule = new AdamUpdate();
if (!(training is BatchDataSet))
{
BatchSize = 25;
}
_method = network;
_flat = network.Flat;
_layerDelta = new double[_flat.LayerOutput.Length];
_gradients = new double[_flat.Weights.Length];
_errorCalculation = new ErrorCalculation();
_rnd = theRandom;
LearningRate = 0.001;
Momentum = 0.9;
}
public UpdateBackStagePass(IUpdateRule next)
: base(next, item => item.Name == "Backstage passes to a TAFKAL80ETC concert")
{
}
public ItemGroup(IEnumerable <Item> items, IUpdateRule rule)
{
Items = items;
Rule = rule;
}
public UpdateSulfuras(IUpdateRule next)
: base(next, item => item.Name == "Sulfuras, Hand of Ragnaros")
{
}
public UpdateDefaultImplementation(IUpdateRule next) : base(next, item => true)
{
}
public UpdateConjuredItem(IUpdateRule next)
: base(next, item => item is ConjuredItem)
{
}
public UpdateAgedBrie(IUpdateRule next) : base(next, item => item.Name == "Aged Brie")
{
}
protected ChainableUpdateRule(IUpdateRule next, Func <Item, bool> predicate)
{
_next = next;
_predicate = predicate;
}
