public void JaccardDistanceTest( )
{
JaccardDistance dist = new JaccardDistance( );
Assert.Throws<ArgumentException>( ( ) => dist.GetDistance( p0, q4 ) );
double result = dist.GetDistance( p0, q0 );
Assert.AreEqual( result, 1 );
result = dist.GetDistance( p1, q1 );
Assert.AreEqual( result, 1 );
result = dist.GetDistance( p2, q2 );
Assert.AreEqual( result, 0 );
result = dist.GetDistance( p3, q3 );
Assert.AreEqual( result, 0 );
result = dist.GetDistance( p4, q4 );
Assert.AreApproximatelyEqual( result, 0.66666, 0.00001 );
result = dist.GetDistance( p5, q5 );
Assert.AreApproximatelyEqual( result, 0.9, 0.1 );
}
/// <summary>
/// JaccardDistance calculation to determine
/// matching similar responses
/// </summary>
/// <param name="input"></param>
/// <param name="memory"></param>
/// <returns></returns>
protected double calculateMatchRateJ(ArrayList input, ArrayList memory)
{
// instantiate new distance class
JaccardDistance dist = new JaccardDistance();
// create two vectors for inputs
//double[] p = new double[] { 2.5, 3.5, 3.0, 3.5, 2.5, 3.0 };
double[] p = DigitizePhonemes(input);
//double[] q = new double[] { 3.0, 3.5, 1.5, 5.0, 3.5, 3.0 };
double[] q = DigitizePhonemes(memory);
List<double> q1 = EqualizeVector(p, q);
double[] q2 = q1.ToArray();
// get distance between the two vectors
double distance = dist.GetDistance(p, q2);
return distance;
}
