public virtual void calc_confidence_method_base(string[] frqitmset, string[] tmpdt, int initial, int stop, int no, int r, int confidence, string[] articles, int a, string file)
{
Apriori inst4 = new Apriori();
Apriori inst5 = new Apriori();
if (no == r)
{
for (int j = 0; j < a; j++)
{
for (int k = 0; k < r; k++)
{
if (articles[j].Equals(tmpdt[k]))
{
return;
}
}
}
inst4.result(confidence, r, file, tmpdt, articles, a);
return;
}
for (int u = initial; u <= stop && stop - u + 1 >= r - no; u++)
{
tmpdt[no] = frqitmset[u];
inst5.calc_confidence_method_base(frqitmset, tmpdt, u + 1, stop, no + 1, r, confidence, articles, a, file);
}
}
// All the methods are defined here
//*******************************************************************************************************************************************************
public virtual void calc_support_method(string[] frqitmset, string[] articles, int initial, int stop, int index, int grpof, int support, string file)
{
Apriori instance_sup = new Apriori();
if (index == grpof)
{
instance_sup.calc_support_method_base(articles, grpof, support, file);
return;
}
for (int i = initial; i <= stop && stop - i + 1 >= grpof - index; i++)
{
articles[index] = frqitmset[i];
instance_sup.calc_support_method(frqitmset, articles, i + 1, stop, index + 1, grpof, support, file);
}
}
public virtual void calc_confidence_method(string[] frqitmset, string[] articles, int initial, int stop, int no, int a, int confidence, string file)
{
Apriori inst3 = new Apriori();
if (no == a)
{
for (int r = 1; r < stop; r++)
{
string[] tmpdt = new string[r];
inst3.calc_confidence_method_base(frqitmset, tmpdt, 0, stop - 1, 0, r, confidence, articles, a, file);
}
return;
}
for (int i = initial; i <= stop && stop - i + 1 >= a - no; i++)
{
articles[no] = frqitmset[i];
inst3.calc_confidence_method(frqitmset, articles, i + 1, stop, no + 1, a, confidence, file);
}
}
//*********************************************************************************************************************
// Main metod starts here
public static void Main(string[] args)
{
// object initialization
Apriori inst1 = new Apriori();
Apriori inst2 = new Apriori();
System.IO.StreamReader br = null;
string readline = "";
string[] articles;
int initial = 0, index = 0;
//initializing count of all items to 0;
int[] count = new int[10];
for (int i = 0; i < 10; i++)
{
count[i] = 0;
}
string sname = "";
int storenumber;
string[] search = new string[] { "Jackets", "Tshirts", "Deo", "Wallet", "Scarf", "Bands", "Cap", "Goggles", "Sneakers", "Giftcards" };
//store selection happens here
//*****************************************************************************************************
Console.WriteLine("Hi! My name is Jarvis ");
Console.WriteLine("Please select the store number(1 to 5) to get the assosiation rules based on apriori algorithm");
Console.WriteLine("1-Target,2-Amazon,3-Alibaba,4-Gap,5-Guess:");
storenumber = Convert.ToInt32(Console.ReadLine());
if (storenumber <= 5)
{
switch (storenumber)
{
case 1:
sname = "Target";
break;
case 2:
sname = "Amazon";
break;
case 3:
sname = "Alibaba";
break;
case 4:
sname = "Gap";
break;
case 5:
sname = "Guess";
break;
default:
Console.WriteLine("You have to choose the correct store number");
break;
}
}
else
{
Console.WriteLine("you have entered wrong store number. It should be a number between 1 to 5");
}
Console.WriteLine("Store number " + storenumber + "->" + sname + " is selected");
Console.WriteLine();
string file = Path.Combine(Environment.CurrentDirectory,
@"..\..\" + sname + ".txt");
//*********************************************************************************************************
// Support and condfidence parameters are enetered here
Console.WriteLine("Enter the Value for Support:");
Console.WriteLine("Note: Values of Support , confidence values must be entered in percentage Ex: 50 ");
int support, confidence;
support = Convert.ToInt32(Console.ReadLine());
Console.WriteLine("Enter the Value for Confidence:");
confidence = Convert.ToInt32(Console.ReadLine());
// File parsing happens here
try
{
br = new System.IO.StreamReader(file); Console.WriteLine();
Console.WriteLine("The Algorithm gives following as result:");
while (!string.ReferenceEquals((readline = br.ReadLine()), null))
{
//each line is read .i.e each transaction in the store is being parsed
articles = readline.Split(',');
for (int i = 0; i < articles.Length; i++)
//each item is selected in a transaction
{
for (int j = 0; j < 10; j++)
{
if (articles[i].Equals(search[j]))
//each item in transaction is compared with all items and when it is found the counter iis increased by 1
{
count[j]++;
}
}
}
}
// now count array has the number of times each item appeared in the transactions
Console.WriteLine("frequent item set(1) with respect to Support value is:");
for (int i = 0; i < 10; i++)
{
if (count[i] > support * 20 / 100)
{
//frequent itemset is collected by pruning
frqitmset[itms] = search[i];
s[itms] = count[i] * 100 / 20;
itms++;
//frequent item set and their suppoer is displayed here
Console.WriteLine(search[i] + " : " + s[itms - 1]);
}
}
int stop = itms - 1;// in terms of array index
Console.WriteLine();
Console.WriteLine("frequent item sets having more than entered Support value: ");
for (int grpof = 2; grpof <= stop; grpof++)
{
articles = new string[grpof];
//This method jons the frequent itemsets in groups of 2 , 3 and so on and gives sets > minimum support value
inst1.calc_support_method(frqitmset, articles, initial, stop, index, grpof, support, file);
}
Console.WriteLine();
Console.WriteLine("Association Rules as per Confidence " + confidence + " %"); Console.WriteLine();
for (int i = 1; i < itms; i++)
{
articles = new string[i];
//This method jons the frequent itemsets in groups of 2 , 3 and so on and gives sets > minimum confidence value
inst2.calc_confidence_method(frqitmset, articles, initial, stop, index, i, confidence, file);
}
Console.WriteLine("Press enter to close...");
Console.ReadLine();
}
catch (Exception e)
{
Console.WriteLine(e.ToString()); Console.Write(e.StackTrace);
}
}