/// <summary>Create a Pearson correlation matrix from given data</summary>
/// <param name="ratings">the ratings data</param>
/// <param name="entity_type">the entity type, either USER or ITEM</param>
/// <param name="shrinkage">a shrinkage parameter</param>
/// <returns>the complete Pearson correlation matrix</returns>
static public CorrelationMatrix Create(IRatings ratings, EntityType entity_type, float shrinkage)
{
Pearson cm;
int num_entities = 0;
if (entity_type.Equals(EntityType.USER))
{
num_entities = ratings.MaxUserID + 1;
}
else if (entity_type.Equals(EntityType.ITEM))
{
num_entities = ratings.MaxItemID + 1;
}
else
{
throw new ArgumentException("Unknown entity type: " + entity_type);
}
try
{
cm = new Pearson(num_entities);
}
catch (OverflowException)
{
Console.Error.WriteLine("Too many entities: " + num_entities);
throw;
}
cm.shrinkage = shrinkage;
cm.ComputeCorrelations(ratings, entity_type);
return(cm);
}
[Test()] public void TestComputeCorrelation()
{
// create test objects
var ratings = new Ratings();
ratings.Add(0, 1, 0.3f);
ratings.Add(0, 4, 0.2f);
ratings.Add(1, 2, 0.6f);
ratings.Add(1, 3, 0.4f);
ratings.Add(1, 4, 0.2f);
// test
var p = new Pearson(ratings.AllUsers.Count, 0f);
Assert.AreEqual(0, p.ComputeCorrelation(ratings, EntityType.USER, 0, 1));
}
[Test()] public void TestCreate()
{
var ratings = new Ratings();
ratings.Add(0, 1, 0.3f);
ratings.Add(0, 2, 0.6f);
ratings.Add(0, 4, 0.2f);
ratings.Add(1, 3, 0.4f);
ratings.Add(1, 4, 0.2f);
ratings.Add(2, 0, 0.1f);
ratings.Add(2, 1, 0.3f);
var correlation_matrix = new Pearson(ratings.MaxUserID + 1, 0f);
correlation_matrix.ComputeCorrelations(ratings, EntityType.USER);
Assert.AreEqual(3, correlation_matrix.NumberOfRows);
Assert.IsTrue(correlation_matrix.IsSymmetric);
Assert.AreEqual(0, correlation_matrix[0, 1]);
}
[Test()] public void TestComputeCorrelations()
{
// create test objects
var pearson = new Pearson(3, 0f);
var rating_data = new Ratings();
rating_data.Add(0, 1, 0.3f);
rating_data.Add(0, 2, 0.6f);
rating_data.Add(0, 4, 0.2f);
rating_data.Add(1, 3, 0.4f);
rating_data.Add(1, 4, 0.2f);
rating_data.Add(2, 0, 0.1f);
rating_data.Add(2, 1, 0.3f);
// test
pearson.Shrinkage = 0;
pearson.ComputeCorrelations(rating_data, EntityType.USER);
Assert.AreEqual(0, pearson[0, 2]);
}
[Test()] public void TestComputeCorrelations2()
{
// load data from disk
var user_mapping = new Mapping();
var item_mapping = new Mapping();
var ratings = RatingData.Read("../../../../data/ml-100k/u1.base", user_mapping, item_mapping);
var p = new Pearson(ratings.AllUsers.Count, 200f);
Assert.AreEqual(-0.02788301f, p.ComputeCorrelation(ratings, EntityType.ITEM, 45, 311), 0.00001);
}
/// <summary>Create a Pearson correlation matrix from given data</summary>
/// <param name="ratings">the ratings data</param>
/// <param name="entity_type">the entity type, either USER or ITEM</param>
/// <param name="shrinkage">a shrinkage parameter</param>
/// <returns>the complete Pearson correlation matrix</returns>
public static CorrelationMatrix Create(IRatings ratings, EntityType entity_type, float shrinkage)
{
Pearson cm;
int num_entities = 0;
if (entity_type.Equals(EntityType.USER))
num_entities = ratings.MaxUserID + 1;
else if (entity_type.Equals(EntityType.ITEM))
num_entities = ratings.MaxItemID + 1;
else
throw new ArgumentException("Unknown entity type: " + entity_type);
try
{
cm = new Pearson(num_entities);
}
catch (OverflowException)
{
Console.Error.WriteLine("Too many entities: " + num_entities);
throw;
}
cm.shrinkage = shrinkage;
cm.ComputeCorrelations(ratings, entity_type);
return cm;
}