public FuzzyTable RemoveRows(int fromIndex, int toIndex)
{
var newTable = new FuzzyTable();
newTable.table = this.table.Clone();
newTable.attributes = new Dictionary <string, FuzzyAttribute>(this.attributes);
newTable.classAttribute = (FuzzyAttribute)this.classAttribute.Clone();
newTable.PositiveColumn = this.PositiveColumn;
newTable.NegativeColumn = this.NegativeColumn;
var rowsToDelete = new List <DataRow>();
for (int i = fromIndex; i < toIndex; i++)
{
var row = this.table.DefaultView[i].Row;
newTable.GetTable().ImportRow(row);
rowsToDelete.Add(row);
}
foreach (var row in rowsToDelete)
{
row.Delete();
}
this.table.AcceptChanges();
return(newTable);
}
public virtual FuzzyTable Clone()
{
var newTable = new FuzzyTable();
newTable.attributes = new Dictionary <string, FuzzyAttribute>(this.attributes);
newTable.classAttribute = (FuzzyAttribute)this.classAttribute.Clone();
newTable.PositiveColumn = this.PositiveColumn;
newTable.NegativeColumn = this.NegativeColumn;
newTable.table = this.table.Copy();
return(newTable);
}
static void Main(string[] args)
{
var table = new FuzzyTable();
try
{ // Open the text file using a stream reader.
using (StreamReader sr = new StreamReader("./data/bupa_fuzzy.json"))
{
String json = sr.ReadToEnd();
dynamic array = JsonConvert.DeserializeObject(json);
for (int i = 0; i < array.attributes.Count - 1; i++)
{
table.addAttribute(array.attributes[i]);
}
table.addClassAttribute(array.attributes[array.attributes.Count - 1], "yes", "no");
table.AddData(array.data);
Console.WriteLine("Started");
var alg = new Algorithm01(0, 0.6);
// var alg = new Algorithm01Modification(0, 0.62, 0.2);
int maxReplications = 30;
int replications = 0;
double TP = 0;
double FP = 0;
double TN = 0;
double FN = 0;
double accuracy = 0;
double sensitivity = 0;
double specificity = 0;
double precision = 0;
for (int i = 0; i < maxReplications; i++)
{
alg.init(table);
var validation01 = new TenCrossValidation();
var matrix = validation01.Validate(10, table, alg);
if (matrix != null)
{
accuracy += matrix.Accuracy();
sensitivity += matrix.Sensitivity();
specificity += matrix.Specificity();
precision += matrix.Precision();
TP += matrix.TruePositivePercent;
FP += matrix.FalsePositivePercent;
TN += matrix.TrueNegativePercent;
FN += matrix.FalseNegativePercent;
replications++;
}
Console.WriteLine(i + " Criteria: " + ((sensitivity / replications) + (specificity / replications)) / 2);
}
Console.WriteLine();
Console.WriteLine("Replications: " + replications);
Console.WriteLine("TP: " + TP / replications);
Console.WriteLine("FP: " + FP / replications);
Console.WriteLine("TN: " + TN / replications);
Console.WriteLine("FN: " + FN / replications);
Console.WriteLine("Accuracy: " + accuracy / replications);
Console.WriteLine("Sensitivity: " + sensitivity / replications);
Console.WriteLine("Specificity: " + specificity / replications);
Console.WriteLine("Precision: " + precision / replications);
Console.WriteLine("Criteria: " + ((sensitivity / replications) + (specificity / replications)) / 2);
return;
}
}
catch (Exception e)
{
Console.WriteLine("The file could not be read:");
Console.WriteLine(e.Message);
Console.WriteLine(e);
}
}
