public Vector GetOutputFromKnownSamples(Sample sample)
{
if (!this.outputs.ContainsKey(sample.Label))
{
this.outputs[sample.Label] = new MappedValue(){ Mean = new Vector(sample.X.Values.ToArray()), Count = 1};
}
else
{
this.outputs[sample.Label].Count++;
int count = this.outputs[sample.Label].Count;
this.outputs[sample.Label].Mean.Multiply(((double)count-1.0)/(double)count);
Vector addPart = new Vector(sample.X.Values.ToArray());
addPart.Multiply(1 / (double)count);
this.outputs[sample.Label].Mean.Add(addPart);
}
return new Vector(this.outputs[sample.Label].Mean.Values.ToArray());
}
/// <summary>
/// Update mean with amnesic average
/// </summary>
/// <param name="vector">Vector, which should be add to mean</param>
protected void UpdateMean(Vector vector)
{
#warning this must be remade according to F. Amnesic average with parameters t1, t2
double t = (double)this.items.Count;
//double multiplier1 = (t - 1) / t;
//double multiplier2 = 1 / t;
double multiplier1 = (t - 1 - this.GetAmnesicParameter(t)) / t;
double multiplier2 = (1 + this.GetAmnesicParameter(t)) / t;
this.mean.Multiply(multiplier1);
Vector incrementPart = new Vector(vector.Values.ToArray());
incrementPart.Multiply(multiplier2);
this.mean.Add(incrementPart);
}