public void setFeatureColumn()
{
ALSWRFactorizer.Features features = new ALSWRFactorizer.Features(factorizer);
var vector = new double[] { 0.5, 2.0, 1.5 };
int index = 1;
features.setFeatureColumnInM(index, vector);
double[][] matrix = features.getM();
Assert.AreEqual(vector[0], matrix[index][0], EPSILON);
Assert.AreEqual(vector[1], matrix[index][1], EPSILON);
Assert.AreEqual(vector[2], matrix[index][2], EPSILON);
}
public void initializeM()
{
ALSWRFactorizer.Features features = new ALSWRFactorizer.Features(factorizer);
double[][] M = features.getM();
Assert.AreEqual(3.333333333, M[0][0], EPSILON);
Assert.AreEqual(5, M[1][0], EPSILON);
Assert.AreEqual(2.5, M[2][0], EPSILON);
Assert.AreEqual(4.333333333, M[3][0], EPSILON);
for (int itemIndex = 0; itemIndex < dataModel.GetNumItems(); itemIndex++) {
for (int feature = 1; feature < 3; feature++ ) {
Assert.True(M[itemIndex][feature] >= 0);
Assert.True(M[itemIndex][feature] <= 0.1);
}
}
}
public void initializeM()
{
ALSWRFactorizer.Features features = new ALSWRFactorizer.Features(factorizer);
double[][] M = features.getM();
Assert.AreEqual(3.333333333, M[0][0], EPSILON);
Assert.AreEqual(5, M[1][0], EPSILON);
Assert.AreEqual(2.5, M[2][0], EPSILON);
Assert.AreEqual(4.333333333, M[3][0], EPSILON);
for (int itemIndex = 0; itemIndex < dataModel.GetNumItems(); itemIndex++)
{
for (int feature = 1; feature < 3; feature++)
{
Assert.True(M[itemIndex][feature] >= 0);
Assert.True(M[itemIndex][feature] <= 0.1);
}
}
}
public void setFeatureColumn()
{
ALSWRFactorizer.Features features = new ALSWRFactorizer.Features(factorizer);
var vector = new double[] { 0.5, 2.0, 1.5 };
int index = 1;
features.setFeatureColumnInM(index, vector);
double[][] matrix = features.getM();
Assert.AreEqual(vector[0], matrix[index][0], EPSILON);
Assert.AreEqual(vector[1], matrix[index][1], EPSILON);
Assert.AreEqual(vector[2], matrix[index][2], EPSILON);
}
public void averageRating()
{
ALSWRFactorizer.Features features = new ALSWRFactorizer.Features(factorizer);
Assert.AreEqual(2.5, features.averateRating(3L), EPSILON);
}
public void averageRating()
{
ALSWRFactorizer.Features features = new ALSWRFactorizer.Features(factorizer);
Assert.AreEqual(2.5, features.averateRating(3L), EPSILON);
}