public void Algorithm02TestFromPublication()
{
var table = new FuzzyTable();
output.WriteLine("Algorithm02TestFromPublication STARTED");
try
{ // Open the text file using a stream reader.
using (StreamReader sr = new StreamReader("../../../Algorithms/tests/test.txt"))
{
String json = sr.ReadToEnd();
dynamic array = JsonConvert.DeserializeObject(json);
// Console.WriteLine(array.attributes);
Assert.True(true);
var aa = array.attributes;
for (int i = 0; i < array.attributes.Count - 1; i++)
{
table.addAttribute(array.attributes[i]);
}
table.addClassAttribute(array.attributes[array.attributes.Count - 1], "Name0", "Name1");
table.AddData(array.data);
var p = new int[20];
for (int i = 0; i < p.Length; i++)
{
p[i] = i;
}
alg02.init(table);
var rules = alg02.process();
for (int i = 0; i < rules.Count; i++)
{
output.WriteLine(rules[i].ToString());
}
var rulesString = "a11 a33 ->c1;a12 a33 ->c2;a12 a31 ->c2;a11 a31 ->c1;a12 a32 ->c1;a11 a32 ->c2;a23 a34 ->c1;a21 a34 ->c2;a22 a34 a54 ->c2;a22 a34 a52 ->c1;a34 a42 ->c2;a11 a23 a32 a41 a54 ->c2;";
var currentRulesString = "";
for (int i = 0; i < rules.Count; i++)
{
currentRulesString += rules[i].ToStringOnlyTerm() + ";";
}
Assert.Equal(rulesString, currentRulesString);
}
}
catch (Exception e)
{
output.WriteLine(e.Message.ToString());
Assert.True(false);
}
}
static void performAlg02(FuzzyTable table, int indexForParam)
{
Console.WriteLine("performAlg02Exp: " + indexForParam);
int size = 11;
Double[] kriteriaArray = new Double[size];
var psi = new Dictionary <string, double>();
psi["no"] = 0.7;
psi["yes"] = 0.7;
for (int i = 0; i < size; i++)
{
var beta = 0.0 + 0.1 * i;
var dataSize = 0;
for (int j = 0; j < 40; j++)
{
Algorithm02 alg02;
switch (indexForParam)
{
case 0:
psi["no"] = beta;
alg02 = new Algorithm02(0, psi);
break;
case 1:
psi["yes"] = beta;
alg02 = new Algorithm02(0, psi);
break;
default:
alg02 = new Algorithm02(0, psi);
break;
}
alg02.init(table);
var validation02 = new TenCrossValidation();
var matrix02 = validation02.Validate(10, table, alg02);
if (matrix02 != null)
{
var kriteria = (matrix02.Sensitivity() + matrix02.Specificity()) / 2;
kriteriaArray[i] += kriteria;
dataSize++;
}
}
Console.WriteLine(indexForParam + " CURRENT beta: " + (beta) + " :" + kriteriaArray[i] / dataSize);
}
}