public Params RunEpoch(DSet <Example> trainSet, ISGDModel <Params> model, Params curParams)
{
Params accumulatedParams =
trainSet.Fold(
(wb, e) => { return(model.Update(wb, e)); },
model.AddParams,
curParams);
var averagedParams = model.ScaleParams(accumulatedParams, (float)(1.0 / trainSet.NumPartitions));
return(averagedParams);
}
public float GetAccuracy(DSet <Example> dataset, ISGDModel <Params> model, Params curParams)
{
int hits = dataset.Fold((c, ex) => model.Predict(curParams, ex) == ex.Label ? c + 1 : c, (c1, c2) => c1 + c2, 0);
return((float)hits / dataset.Count());
}
/// <summary>
/// The "prior" of a dataset is simply the number of positive examples divided by the size of the dataset.
/// </summary>
/// <param name="examples"></param>
/// <returns></returns>
private static float GetPrior(DSet <Example> examples)
{
long hits = examples.Fold((c, ex) => ex.Label == 1.0f ? c + 1 : c, (c1, c2) => c1 + c2, 0);
return((float)hits / examples.Count());
}