static void Main(string[] args)
{
bool isDebug = false;
FileHandling.ReadFile(isDebug);
//DataSet.PrintSimpleStructure();
Algorithm algorithm = new Algorithm();
Algorithm.ID3(DataSet.RootNode, new DataBag(DataSet.Instances));
Printer.BeautifulBorder("ID3:");
Printer.Print(DataSet.RootNode);
var b = new Bayes();
var con = new ConfusionMatrix();
Printer.BeautifulBorder("Naïve Bayes:");
con.PrintMatrix();
b.PrintLikelihoodTable();
Console.WriteLine(
b.ClassifyDataInstance(new DataInstance(new List <string>()
{
"rainy", "mild", "normal", "true"
})));
if (!isDebug)
{
Console.Read();
}
}
public ConfusionMatrix()
{
var bayes = new Bayes();
_matrix = new int[_dimensionSize, _dimensionSize];
var instanceSum = DataSet.Instances.Count;
float truePos = 0, trueNeg = 0, falsePos = 0, falseNeg = 0;
foreach (var instance in DataSet.Instances)
{
var outcome = bayes.ClassifyDataInstance(instance);
if (outcome == instance.Qualifier)
{
truePos++;
trueNeg += (_dimensionSize - 1);
}
else
{
falsePos++;
falseNeg++;
trueNeg += (_dimensionSize - 2);
//Console.WriteLine($"Wrong: {DataSet.Instances.IndexOf(instance)}");
}
_matrix[instance.Qualifier, outcome]++;
}
RealAccuracy = (100 * truePos / (truePos + falsePos));
Accuracy = (100 * (truePos + trueNeg) / (truePos + trueNeg + falsePos + falseNeg));
}
