public void TestSparsify()
{
string[] target = iris.Target.Select(t => iris.TargetNames[t]).ToArray();
var clf = new LogisticRegression <string>(random: new Random(0));
clf.Fit(iris.Data, target);
Matrix <double> predDD = clf.DecisionFunction(iris.Data);
clf.Sparsify();
Assert.IsInstanceOfType(clf.Coef, typeof(SparseMatrix));
Matrix <double> predSD = clf.DecisionFunction(iris.Data);
Matrix spData = SparseMatrix.OfMatrix(iris.Data);
Matrix <double> predSS = clf.DecisionFunction(spData);
clf.Densify();
Matrix <double> predDS = clf.DecisionFunction(spData);
Assert.IsTrue(predDD.AlmostEquals(predSD));
Assert.IsTrue(predDD.AlmostEquals(predSS));
Assert.IsTrue(predDD.AlmostEquals(predDS));
}
public void TestSparsify()
{
string[] target = iris.Target.Select(t => iris.TargetNames[t]).ToArray();
var clf = new LogisticRegression<string>(random: new Random(0));
clf.Fit(iris.Data, target);
Matrix<double> predDD = clf.DecisionFunction(iris.Data);
clf.Sparsify();
Assert.IsInstanceOfType(clf.Coef, typeof(SparseMatrix));
Matrix<double> predSD = clf.DecisionFunction(iris.Data);
Matrix spData = SparseMatrix.OfMatrix(iris.Data);
Matrix<double> predSS = clf.DecisionFunction(spData);
clf.Densify();
Matrix<double> predDS = clf.DecisionFunction(spData);
Assert.IsTrue(predDD.AlmostEquals(predSD));
Assert.IsTrue(predDD.AlmostEquals(predSS));
Assert.IsTrue(predDD.AlmostEquals(predDS));
}