public void testFullCorrelation2()
{
IDataModel dataModel = getDataModel(
new long[] {1, 2},
new Double?[][] {
new double?[]{1.0, 2.0, 3.0},
new double?[]{1.0},
});
double correlation = new TanimotoCoefficientSimilarity(dataModel).UserSimilarity(1, 2);
assertCorrelationEquals(0.3333333333333333, correlation);
}
public void testCorrelation2()
{
IDataModel dataModel = getDataModel(
new long[] {1, 2},
new Double?[][] {
new double?[]{null, 2.0, 3.0, 1.0},
new double?[]{1.0, 1.0, null, 0.0},
});
double correlation = new TanimotoCoefficientSimilarity(dataModel).UserSimilarity(1, 2);
Assert.AreEqual(0.5, correlation, EPSILON);
}
public void testCorrelation2()
{
IDataModel dataModel = getDataModel(
new long[] { 1, 2 },
new Double?[][] {
new double?[] { null, 2.0, 3.0, 1.0 },
new double?[] { 1.0, 1.0, null, 0.0 },
});
double correlation = new TanimotoCoefficientSimilarity(dataModel).UserSimilarity(1, 2);
Assert.AreEqual(0.5, correlation, EPSILON);
}
public void testFullCorrelation2()
{
IDataModel dataModel = getDataModel(
new long[] { 1, 2 },
new Double?[][] {
new double?[] { 1.0, 2.0, 3.0 },
new double?[] { 1.0 },
});
double correlation = new TanimotoCoefficientSimilarity(dataModel).UserSimilarity(1, 2);
assertCorrelationEquals(0.3333333333333333, correlation);
}
public void testReturnNaNDoubleWhenNoSimilaritiesForTwoItems()
{
IDataModel dataModel = getDataModel(
new long[] { 1, 2 },
new Double?[][] {
new double?[] { null, null, 3.0 },
new double?[] { 1.0, 1.0, null },
});
Double similarity = new TanimotoCoefficientSimilarity(dataModel).ItemSimilarity(1, 2);
Assert.AreEqual(Double.NaN, similarity, EPSILON);
}
public Result RecommendTanimotoSimilarity(int userId, int movieId)
{
Result result = new Result();
dataModel = new FileDataModel(PathToDataFile, false, FileDataModel.DEFAULT_MIN_RELOAD_INTERVAL_MS, false, ",", userId, movieId);
var removedPrefs = GenericDataModel.preferenceFromUsersRemoved.Values;
var valueToCompare = removedPrefs.FirstOrDefault(i => i.GetItemID() == movieId).GetValue();
var similarity = new TanimotoCoefficientSimilarity(dataModel);
var recommender = new GenericItemBasedRecommender(dataModel, similarity);
var preferences = recommender.EstimatePreference(userId, movieId);
result.PredictedValue = preferences;
result.RealValue = removedPrefs.First().GetValue();
return result;
}
public void testItemsSimilarities()
{
IDataModel dataModel = getDataModel(
new long[] { 1, 2 },
new Double?[][] {
new double?[] { 2.0, null, 2.0 },
new double?[] { 1.0, 1.0, 1.0 },
});
TanimotoCoefficientSimilarity tCS = new TanimotoCoefficientSimilarity(dataModel);
Assert.AreEqual(0.5, tCS.ItemSimilarity(0, 1), EPSILON);
Assert.AreEqual(1, tCS.ItemSimilarity(0, 2), EPSILON);
double[] similarities = tCS.ItemSimilarities(0, new long [] { 1, 2 });
Assert.AreEqual(0.5, similarities[0], EPSILON);
Assert.AreEqual(1, similarities[1], EPSILON);
}
public void testItemsSimilarities()
{
IDataModel dataModel = getDataModel(
new long[] {1, 2},
new Double?[][] {
new double?[]{2.0, null, 2.0},
new double?[]{1.0, 1.0, 1.0},
});
TanimotoCoefficientSimilarity tCS = new TanimotoCoefficientSimilarity(dataModel);
Assert.AreEqual(0.5, tCS.ItemSimilarity(0, 1), EPSILON);
Assert.AreEqual(1, tCS.ItemSimilarity(0, 2), EPSILON);
double[] similarities = tCS.ItemSimilarities(0, new long [] {1, 2});
Assert.AreEqual(0.5, similarities[0], EPSILON);
Assert.AreEqual(1, similarities[1], EPSILON);
}
public void testReturnNaNDoubleWhenNoSimilaritiesForTwoItems()
{
IDataModel dataModel = getDataModel(
new long[] {1, 2},
new Double?[][] {
new double?[]{null, null, 3.0},
new double?[]{1.0, 1.0, null},
});
Double similarity = new TanimotoCoefficientSimilarity(dataModel).ItemSimilarity(1, 2);
Assert.AreEqual(Double.NaN, similarity, EPSILON);
}