public void Train(IUserItemRelation data)
{
var deviationsMatrix = data.Secondary.Select(item => CreateVector(item, data))
.CrossPairwise((vector1, vector2) => ComputeDeviations(vector1, vector2))
.ToMatrix(t => t.Item1, t => t.Item2, t => t.Item3);
throw new NotImplementedException();
}
private NamedVector <NamedValue> CreateVector(Item item, IUserItemRelation data)
{
var associated = data.Association
.Where(jr => item.Name.Equals(jr.Second.Name));
return(new NamedVector <NamedValue>(item.Name,
associated.Select(jr => new NamedValue(jr.First.Name, jr.Value))
.ToList()));
}
public Matrix <double> BuildSimilarityMatrix(IUserItemRelation data)
{
var userAverages = data.Primary.ToDictionary(u => u.Name,
u => data.Association.GetRecords(u).Average(jr => jr.Value));
return(data.Secondary.Select(item => CreateVector(item, data))
.CrossPairwise((vector1, vector2) => ComputeSimilarity(vector1, vector2, userAverages))
.ToMatrix());
}
public void Train(IUserItemRelation data)
{
_correlationLookup = ConvertToVectors(data)
.CrossPairwise((vector1, vector2) => _algorithm.ComputeCorrelation(vector1, vector2))
.ToCorrelationLookup();
_bundledItems = data.Primary.Select(u => CreateBundledItem(u, data.Association))
.ToDictionary(b => b.Item.Name);
IsTrained = true;
}
public void Train(IUserItemRelation data)
{
_items = data.Secondary.ToDictionary(i => i.Name);
_similarityMatrix = _algorithm.BuildSimilarityMatrix(data);
IsTrained = true;
}