public void TestMethodAlgorithms()
{
List <double> supports = new List <double>(new double[] { 0.001, 0.002, 0.003, 0.004, 0.005, 0.01, 0.02, 0.03, 0.04, 0.05, 0.1, 0.2 });
string stringResult = "";
foreach (double support in supports)
{
var start = DateTime.Now;
var transactions = new TransactionDatabase(@"\\small.txt");
var apriori = new Apriori(transactions, 0.2);
apriori.Run();
var end = DateTime.Now;
var result = end - start;
stringResult += $"APRIORI Support:{support} Total Time (ms): {result.TotalMilliseconds}" + Environment.NewLine;
}
foreach (double support in supports)
{
var start = DateTime.Now;
var transactions = new TransactionDatabase(@"\\small.txt");
var eclat = new Eclat(transactions, 0.2);
eclat.Run();
var end = DateTime.Now;
var result = end - start;
stringResult += $"ECLAT Support:{support} Total Time (ms): {result.TotalMilliseconds}" + Environment.NewLine;
System.IO.File.WriteAllText(@"PerformanceResultsAuto.csv", stringResult);
}
}
private void performanceTestToolStripMenuItem_Click(object sender, EventArgs e)
{
List <double> supports = new List <double>(new double[] { 0.01, 0.02, 0.03, 0.04, 0.05, 0.1, 0.2, 0.3, 0.4, 0.5 });
string stringResult = "";
string readfile = File.ReadAllText(comboBoxTestDataSet.Text);
foreach (double support in supports)
{
var start = DateTime.Now;
var transactions = new TransactionDatabase(comboBoxTestDataSet.Text);
var apriori = new Apriori(transactions, support);
apriori.Run();
var end = DateTime.Now;
var result = end - start;
var resultMem = GC.GetTotalMemory(true);
stringResult += $"APRIORI Support:{support} Total Time (ms): {result.TotalMilliseconds} Memory Usage (bytes): {resultMem}" + Environment.NewLine;
}
foreach (double support in supports)
{
var start = DateTime.Now;
var transactions = new TransactionDatabase(comboBoxTestDataSet.Text);
var eclat = new Eclat(transactions, support);
eclat.Run();
var end = DateTime.Now;
var result = end - start;
var resultMem = GC.GetTotalMemory(true);
stringResult += $"ECLAT Support:{support} Total Time (ms): {result.TotalMilliseconds} Memory Usage (bytes): {resultMem}" + Environment.NewLine;
System.IO.File.WriteAllText(@"PerformanceResults.txt", stringResult);
}
}
private void eCLATAlgorithmToolStripMenuItem_Click(object sender, EventArgs e)
{
var transactions = new TransactionDatabase(comboBoxTestDataSet.Text);
var eclat = new Eclat(transactions, double.Parse(textBoxMinimumSupport.Text));
eclat.Run();
textBoxOutput.AppendText(eclat.ToString());
csvString = eclat.ToCSV();
}
public void Eclat_Calcuates_Transactions_Support_Right()
{
var transactions = new TransactionDatabase();
transactions.AddTransaction(new Transaction("A,B,C,D"));
transactions.AddTransaction(new Transaction("A,B,C,A"));
transactions.AddTransaction(new Transaction("A,B"));
transactions.AddTransaction(new Transaction("A,B,C"));
transactions.AddTransaction(new Transaction("D"));
transactions.AddTransaction(new Transaction("E"));
var eclat = new Eclat(transactions);
eclat.Run();
Assert.IsTrue(eclat.IsTransactionSupported(new Transaction("A,B")), "Apriori algorithm did not works right as new Transaction(\"A,B\") is not included in Supported Transactions List");
Assert.IsFalse(eclat.IsTransactionSupported(new Transaction("D,E")), "Apriori algorithm did not works right as new Transaction(\"D,E\") is included in Supported Transactions List");
}
public void Eclat_Creation_Default_Constructor_Name()
{
var transactions = new TransactionDatabase();
transactions.AddTransaction(new Transaction("A,B,C,D"));
transactions.AddTransaction(new Transaction("A,B,C,A"));
transactions.AddTransaction(new Transaction("A,B"));
transactions.AddTransaction(new Transaction("A,B,C"));
transactions.AddTransaction(new Transaction("D"));
transactions.AddTransaction(new Transaction("E"));
var eclat = new Eclat(transactions, 0.2);
eclat.Run();
Assert.AreEqual(8, eclat.TransactionCountWithSupport(), "Apriori Algorithm results wrong amount of transaction.");
eclat = new Eclat(transactions);
eclat.Run();
Assert.AreEqual(16, eclat.TransactionCountWithSupport(), "Apriori Algorithm results wrong amount of transaction.");
Assert.IsTrue(eclat.IsTransactionSupported(new Transaction("A,B")), "Apriori algorithm did not works right as new Transaction(\"A,B\") is not included in Supported Transactions List");
}
public void Process(string input)
{
input = input.Trim();
if (input == "")
{
return;
}
else if (input.ToLower() == "listdatasets")
{
if (ApplicationConfiguration.DataFiles.Count == 0)
{
Output.AppendText("------------------" + Environment.NewLine);
Output.AppendText("List of Currently Availabe Data Files Are:" + Environment.NewLine);
}
else
{
Output.AppendText("------------------" + Environment.NewLine);
Output.AppendText("List of Currently Availabe Data Files Are:" + Environment.NewLine);
for (var i = 1; i <= ApplicationConfiguration.DataFiles.Count; i++)
{
Output.AppendText(i + ". " + ApplicationConfiguration.DataFiles[i - 1] + Environment.NewLine);
}
}
}
else if (input.ToLower().Substring(0, 8) == "listfile")
{
var fileName = input.ToLower().Substring(9, input.Length - 10);
var fullFileName = Application.StartupPath + "\\" + fileName;
Output.AppendText("------------------" + Environment.NewLine);
if (File.Exists(fullFileName))
{
Output.AppendText("The contents of the file " + fileName + " are" + Environment.NewLine);
Output.AppendText(File.ReadAllText(fullFileName) + Environment.NewLine);
}
else
{
Output.AppendText("File " + fileName + " cannot be found" + Environment.NewLine);
}
Output.AppendText("------------------" + Environment.NewLine);
}
else if (input.ToLower().Substring(0, 11) == "listdataset")
{
var datasetNumber = input.ToLower().Substring(12, input.Length - 13);
int intDataSetNumber;
bool isNumeric = int.TryParse(datasetNumber, out intDataSetNumber);
Output.AppendText("------------------" + Environment.NewLine);
if (isNumeric)
{
if (intDataSetNumber <= ApplicationConfiguration.DataFiles.Count)
{
var fullFileName = Application.StartupPath + "\\" + ApplicationConfiguration.DataFiles[intDataSetNumber - 1];
if (File.Exists(fullFileName))
{
Output.AppendText("The contents of the dataset " + ApplicationConfiguration.DataFiles[intDataSetNumber - 1] + " are" + Environment.NewLine);
Output.AppendText(File.ReadAllText(fullFileName) + Environment.NewLine);
}
else
{
Output.AppendText("The contents of the dataset cannot be found!" + Environment.NewLine);
}
}
else
{
Output.AppendText("Dataset with " + intDataSetNumber + " cannot be found" + Environment.NewLine);
}
}
else
{
Output.AppendText(datasetNumber + " is not numeric" + Environment.NewLine);
Output.AppendText("------------------" + Environment.NewLine);
}
}
else if (input.ToLower().Substring(0, 7) == "apriori")
{
var parameters = Regex.Match(input.ToLower(), @"\(([^)]*)\)").Groups[1].Value;
var dataSet = parameters.Substring(0, parameters.LastIndexOf(","));
double support = double.Parse(parameters.Substring(parameters.LastIndexOf(",") + 1, parameters.Length - parameters.LastIndexOf(",") - 1));
int intDataSetNumber;
bool isNumeric = int.TryParse(dataSet, out intDataSetNumber);
string fileName;
if (isNumeric)
{
fileName = ApplicationConfiguration.DataFiles[intDataSetNumber - 1];
}
else
{
fileName = Regex.Match(parameters, @"\""([^)]*)\""").Groups[1].Value;
}
Output.AppendText("------------------" + Environment.NewLine);
if (intDataSetNumber <= ApplicationConfiguration.DataFiles.Count)
{
var fullFileName = Application.StartupPath + "\\" + fileName;
if (File.Exists(fullFileName))
{
Output.AppendText("The result of the dataset " + fileName + " are" + Environment.NewLine);
var transactions = new TransactionDatabase(fileName);
var apriori = new Apriori(transactions, support);
apriori.Run();
Output.AppendText(apriori.ToString());
}
else
{
Output.AppendText("The contents of the dataset cannot be found!" + Environment.NewLine);
}
}
else
{
Output.AppendText("Dataset with " + intDataSetNumber + " cannot be found" + Environment.NewLine);
}
}
else if (input.ToLower().Substring(0, 5) == "eclat")
{
var parameters = Regex.Match(input.ToLower(), @"\(([^)]*)\)").Groups[1].Value;
var dataSet = parameters.Substring(0, parameters.LastIndexOf(","));
double support = double.Parse(parameters.Substring(parameters.LastIndexOf(",") + 1, parameters.Length - parameters.LastIndexOf(",") - 1));
int intDataSetNumber;
bool isNumeric = int.TryParse(dataSet, out intDataSetNumber);
string fileName;
if (isNumeric)
{
fileName = ApplicationConfiguration.DataFiles[intDataSetNumber - 1];
}
else
{
fileName = Regex.Match(parameters, @"\""([^)]*)\""").Groups[1].Value;
}
Output.AppendText("------------------" + Environment.NewLine);
if (intDataSetNumber <= ApplicationConfiguration.DataFiles.Count)
{
var fullFileName = Application.StartupPath + "\\" + fileName;
if (File.Exists(fullFileName))
{
Output.AppendText("The result of the dataset " + fileName + " are" + Environment.NewLine);
var transactions = new TransactionDatabase(fileName);
var eclat = new Eclat(transactions, support);
eclat.Run();
Output.AppendText(eclat.ToString());
}
else
{
Output.AppendText("The contents of the dataset cannot be found!" + Environment.NewLine);
}
}
else
{
Output.AppendText("Dataset with " + intDataSetNumber + " cannot be found" + Environment.NewLine);
}
}
else
{
Output.AppendText("------------------" + Environment.NewLine);
Output.AppendText("Unknown Command" + Environment.NewLine);
Output.AppendText("------------------" + Environment.NewLine);
}
}
}//DMForm
//Methods *************************************************************
//Events **************************************************************
private void btnExecute_Click(object sender, EventArgs e)
{
if (cmbAlgorithm.SelectedItem == null)
{
MessageBox.Show("Please select an algorithm.");
return;
}//if no algorithm
string algorithm = cmbAlgorithm.SelectedItem.ToString();
if (algorithm.Equals("Apriori"))
{
rtbResults.Text = "";
List <ItemSetDto> results = new List <ItemSetDto>();
DateTime timer = DateTime.Now;
if (cmbSource.SelectedItem == null)
{
MessageBox.Show("Please select a data source.");
return;
}//if
if (txtMinSupport.Text.Equals(""))
{
MessageBox.Show("Please enter a Minimum Support");
return;
}//if
double minSupport = Convert.ToDouble(txtMinSupport.Text);
string datasource = cmbSource.SelectedItem.ToString();
DataSourceBLL dsBLL = new DataSourceBLL();
Apriori ap = new Apriori();
List <TransactionDto> transactions = dsBLL.process(datasource);
if (transactions == null)
{
return;
}
results = ap.Process(transactions, null, minSupport);
StringBuilder sb = new StringBuilder();
foreach (ItemSetDto isd in results)
{
sb.AppendLine(isd.toString());
}
rtbResults.AppendText(sb.ToString() + "\nTime to Complete: " + (DateTime.Now - timer).ToString());
}//if "Apriori"
else if (algorithm.Equals("FPGrowth"))
{
if (txtMinSupport.Text.Equals(""))
{
MessageBox.Show("Please enter a Minimum Support");
return;
}//if
double minSupport = Convert.ToDouble(txtMinSupport.Text);
string datasource = cmbSource.SelectedItem.ToString();
DataSourceBLL dsBLL = new DataSourceBLL();
List <TransactionDto> dtos = dsBLL.process(datasource);
if (dtos == null)
{
return;
}
rtbResults.Text = "";
DateTime timer = DateTime.Now;
FPGrowth fpg = new FPGrowth(dtos, minSupport);
List <FrequentPattern> fp = fpg.mine();
StringBuilder sb = new StringBuilder();
foreach (FrequentPattern f in fp)
{
sb.AppendLine(f.ToString());
}
rtbResults.AppendText(sb.ToString() + "\nTime to Complete: " + (DateTime.Now - timer).ToString());
}//if "FPGrowth"
else if (algorithm.Equals("Eclat"))
{
rtbResults.Text = "";
List <VerticalItemSetDto> results = new List <VerticalItemSetDto>();
DateTime timer = DateTime.Now;
if (cmbSource.SelectedItem == null)
{
MessageBox.Show("Please select a data source.");
return;
}//if
if (txtMinSupport.Text.Equals(""))
{
MessageBox.Show("Please enter a Minimum Support");
return;
}//if
double minSupport = Convert.ToDouble(txtMinSupport.Text);
string datasource = cmbSource.SelectedItem.ToString();
DataSourceBLL dsBLL = new DataSourceBLL();
Eclat ec = new Eclat();
List <TransactionDto> transactions = dsBLL.process(datasource);
if (transactions == null)
{
return;
}
results = ec.Process(transactions, null, minSupport);
StringBuilder sb = new StringBuilder();
foreach (VerticalItemSetDto isd in results)
{
sb.AppendLine(isd.toString());
}
rtbResults.AppendText(sb.ToString() + "\nTime to Complete: " + (DateTime.Now - timer).ToString());
} //if "Eclat"
} //btnExecute_Click
public void EX_Rules(double support, double confidence, double max_confidence, double negsupport, double negconfidence, double negmax_confidence)
{
List <Transaction> data = new List <Transaction>();
List <Rule> eclat_rules = new List <Rule>();
List <Itemset> eclat_Litemsets = new List <Itemset>();
List <Rule> negeclat_rules = new List <Rule>();
List <Itemset> negeclat_Litemsets = new List <Itemset>();
data = list2mat(tr_messages, "train");
Eclat eclat = new Eclat(data, labels, support, confidence);
eclat = eclat.Run(support, confidence);
eclat_rules = eclat.eclat_rules;
eclat_Litemsets = eclat.L_itemsets;
//Pruning Rules
for (int i = 0; i < eclat_Litemsets.Count; i++)
{
var item = eclat_Litemsets[i];
if (item.confidence >= max_confidence)
{
List <string> temp2 = item.items;
for (int jj = i + 1; jj < eclat_Litemsets.Count; jj++)
{
List <string> temp1 = eclat_Litemsets[jj].items;
bool flag = true;
foreach (string s in temp2)
{
if (!temp1.Contains(s))
{
flag = false;
break;
}
}
if (flag)
{
eclat_Litemsets.RemoveAt(jj);
}
}
}
}
//Negative Rules
int[] neglabels = new int[labels.Length];
for (int i = 0; i < labels.Length; i++)
{
if (labels[i] == 0)
{
neglabels[i] = 1;
}
}
Eclat negeclat = new Eclat(data, neglabels, negsupport, negconfidence);
negeclat = negeclat.Run(negsupport, negconfidence);
negeclat_rules = negeclat.eclat_rules;
negeclat_Litemsets = negeclat.L_itemsets;
//Pruning Rules
for (int i = 0; i < negeclat_Litemsets.Count; i++)
{
var item = negeclat_Litemsets[i];
if (item.confidence >= negmax_confidence)
{
List <string> temp2 = item.items;
for (int jj = i + 1; jj < negeclat_Litemsets.Count; jj++)
{
List <string> temp1 = negeclat_Litemsets[jj].items;
bool flag = true;
foreach (string s in temp2)
{
if (!temp1.Contains(s))
{
flag = false;
break;
}
}
if (flag)
{
negeclat_Litemsets.RemoveAt(jj);
}
}
}
}
//write model
System.IO.File.Delete("AR.model");
string[] row = new string[negeclat_Litemsets.Count + eclat_Litemsets.Count];
for (int i = 0; i < eclat_Litemsets.Count; i++)
{
var item = eclat_Litemsets[i];
row[i] = "Pos&" + "{" + string.Join(",", item.items) + "}&" + item.support.ToString() + "&" + item.confidence.ToString("0.0000");
}
for (int i = 0; i < negeclat_Litemsets.Count; i++)
{
var item = negeclat_Litemsets[i];
row[eclat_Litemsets.Count + i] = "Neg&" + "{" + string.Join(",", item.items) + "}&" + item.support.ToString() + "&" + item.confidence.ToString("0.0000");
}
System.IO.File.WriteAllLines("AR.model", row);
eclatlitems = eclat_Litemsets;
foreach (var rule in negeclat_Litemsets)
{
eclatlitems.Add(new Itemset(rule.items, rule.support, -rule.confidence));
}
//return eclatlitems;
docRule = calculate_docrule(data);
//classification_train(docRule, labels, algoritm);
}
